AIICS

Patrick Doherty

Conference and Workshop Publications

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2023
[148] Adeline Secolo, Paulo Santos, Patrick Doherty and Zoran Sjanic. 2023.
Collaborative Qualitative Environment Mapping.
In AI 2023: Advances in Artificial Intelligence, pages 3–15. In series: Lecture Notes in Computer Science #??. Springer. ISBN: 9789819983902, 9789819983919.
DOI: 10.1007/978-981-99-8391-9_1.
Note: Funding Agencies|CISB, Swedish-Brazilian Research and Innovation Center; Saab AB; Coordenacao de Aperfeicoamento de Pessoal em Nivel Superior - Brasil (CAPES) [001]

This paper explores the use of LH Interval Calculus, a novel qualitative spatial reasoning formalism, to create a human-readable representation of environments observed by UAVs. The system simplifies data from multiple UAVs collaborating on environment mapping. Real UAV-captured data was used for evaluation. In tests involving two UAVs mapping an outdoor area, LH Calculus proved effective in generating a cohesive high-level description of the environment, contingent on consistent input data.

2020
[147] Patrick Doherty and Andrzej Szalas. 2020.
Rough Forgetting.
In Rough Sets. IJCRS 2020, pages 3–18. In series: Lecture Notes in Computer Science #12179. Springer. ISBN: 9783030527051, 9783030527044.
DOI: 10.1007/978-3-030-52705-1_1.
Note: ELLIIT Network Organization for Information and Communication Technology, Sweden; Swedish Foundation for Strategic Research SSFSwedish Foundation for Strategic Research; Jinan University (Zhuhai Campus) [2017/27/B/ST6/02018]; National Science Centre PolandNational Science Centre, Poland
Fulltext: https://doi.org/10.1007/978-3-030-52705-...

Recent work in the area of Knowledge Representation and Reasoning has focused on modification and optimization of knowledge bases (KB) through the use of forgetting operators of the form forget(KB, (R) over bar), where (R) over bar is a set of relations in the language signature used to specify the KB. The result of this operation is a new KB where the relations in (R) over bar are removed from the KB in a principled manner resulting in a more efficient representation of the KB for different purposes. The forgetting operator is also reflected semantically in terms of the relation between the original models of the KB and the models for the revised KB after forgetting. In this paper, we first develop a rough reasoning framework where our KBs consist of rough formulas with a semantics based on a generalization of Kleene algebras. Using intuitions from the classical case, we then define a forgetting operator that can be applied to rough KBs removing rough relations. A constructive basis for generating a new KB as the result of applying the forgetting operator to a rough KB is specified using second-order quantifier elimination techniques. We show the application of this technique with some practical examples.

[146] Olov Andersson, Per Sidén, Johan Dahlin, Patrick Doherty and Mattias Villani. 2020.
Real-Time Robotic Search using Structural Spatial Point Processes.
In 35TH UNCERTAINTY IN ARTIFICIAL INTELLIGENCE CONFERENCE (UAI 2019), pages 995–1005. In series: Proceedings of Machine Learning Research (PMLR) #115. Association For Uncertainty in Artificial Intelligence (AUAI).
Note: Funding: Wallenberg AI, Autonomous Systems and Software Program (WASP); WASP Autonomous Research Arenas - Knut and Alice Wallenberg Foundation; Swedish Foundation for Strategic Research (SSF)Swedish Foundation for Strategic Research; ELLIIT Excellence Center at Link opingLund for Information Technology
Link: http://auai.org/uai2019/proceedings/pape...

Aerial robots hold great potential for aiding Search and Rescue (SAR) efforts over large areas, such as during natural disasters. Traditional approaches typically search an area exhaustively, thereby ignoring that the density of victims varies based on predictable factors, such as the terrain, population density and the type of disaster. We present a probabilistic model to automate SAR planning, with explicit minimization of the expected time to discovery. The proposed model is a spatial point process with three interacting spatial fields for i) the point patterns of persons in the area, ii) the probability of detecting persons and iii) the probability of injury. This structure allows inclusion of informative priors from e.g. geographic or cell phone traffic data, while falling back to latent Gaussian processes when priors are missing or inaccurate. To solve this problem in real-time, we propose a combination of fast approximate inference using Integrated Nested Laplace Approximation (INLA), and a novel Monte Carlo tree search tailored to the problem. Experiments using data simulated from real world Geographic Information System (GIS) maps show that the framework outperforms competing approaches, finding many more injured in the crucial first hours.

2019
[145] Mariusz Wzorek, Cyrille Berger and Patrick Doherty. 2019.
Router Node Placement in Wireless Mesh Networks for Emergency Rescue Scenarios.
In PRICAI 2019: TRENDS IN ARTIFICIAL INTELLIGENCE, PT II, pages 496–509. In series: Lecture Notes in Artificial Intelligence #??. SPRINGER INTERNATIONAL PUBLISHING AG. ISBN: 978-3-030-29911-8, 978-3-030-29910-1.
DOI: 10.1007/978-3-030-29911-8_38.
Note: Funding Agencies|ELLIIT network organization for Information and Communication Technology; Swedish Foundation for Strategic ResearchSwedish Foundation for Strategic Research [RIT 15-0097]; Autonomous Systems and Software Program (WASP) - Knut and Alice Wallenberg Foundation

The focus of this paper is on base functionalities required for UAV-based rapid deployment of an ad hoc communication infrastructure in the initial phases of rescue operations. The general idea is to use heterogeneous teams of UAVs to deploy communication kits that include routers. These kits will then be used in the generation of ad hoc Wireless Mesh Networks. A fundamental problem, known as the Router Node Placement problem (RNP) is to determine how one can optimally place such routers. An extended version of the RNP problem is specified that takes into account additional constraints that arise in actual field usage. This extended problem is solved with a new algorithm, RRT-WMN, based on a novel use of the Rapidly Exploring Random Trees (RRT) algorithm used in motion planning. A comparative empirical evaluation between RRT-WMN and existing techniques, CMA-ES and PSO, shows that the RRT-WMN algorithm has far better performance both in time and coverage as the extended RNP problem scales to realistic scenarios.

[144] Piotr Rudol and Patrick Doherty. 2019.
Evaluation of Human Body Detection Using Deep Neural Networks with Highly Compressed Videos for UAV Search and Rescue Missions.
In PRICAI 2019: TRENDS IN ARTIFICIAL INTELLIGENCE, PT III, pages 402–417. In series: Lecture Notes in Artificial Intelligence #??. SPRINGER INTERNATIONAL PUBLISHING AG. ISBN: 978-3-030-29894-4, 978-3-030-29893-7.
DOI: 10.1007/978-3-030-29894-4_33.
Note: Funding Agencies|ELLIIT network organization for Information and Communication Technology; Swedish Foundation for Strategic Research (SymbiKBot Project); Wallenberg AI, Autonomous Systems and Software Program (WASP) - Research Arena Public Safety (WARA-PS)

Dealing with compressed video streams in mobile robotics is an unavoidable fact of life. Transferring images between mobile robots or to the Cloud using wireless links can practically only be achieved using lossy video compression. This introduces artifacts that often make image processing challenging. Recent algorithms based on deep neural networks, as advanced as they are, are commonly trained and evaluated on datasets of high-fidelity images which are typically not captured from aerial views. In this work we evaluate a number of deep neural network based object detection algorithms in the context of aerial search and rescue scenarios where real-time and robust detection of human bodies is a priority. We provide an evaluation using a number of video sequences collected in-flight using Unmanned Aerial Vehicle (UAV) platforms in different environmental conditions. We also describe the detection performance degradation under limited bitrate compression using H.264, H.265 and VP9 video codecs, in addition to analyzing the timing effects of moving image processing tasks to off-board entities.

[143] Olov Andersson and Patrick Doherty. 2019.
Deep RL for Autonomous Robots: Limitations and Safety Challenges.
In , pages 489–495. ESANN. ISBN: 9782875870650.

With the rise of deep reinforcement learning, there has also been a string of successes on continuous control problems using physics simulators. This has lead to some optimism regarding use in autonomous robots and vehicles. However, to successful apply such techniques to the real world requires a firm grasp of their limitations. As recent work has raised questions of how diverse these simulation benchmarks really are, we here instead analyze a popular deep RL approach on toy examples from robot obstacle avoidance. We find that these converge very slowly, if at all, to safe policies. We identify convergence issues on stochastic environments and local minima as problems that warrant more attention for safety-critical control applications.

2018
[142] Mariusz Wzorek, Cyrille Berger, Piotr Rudol and Patrick Doherty. 2018.
Deployment of Ad Hoc Network Nodes Using UAVs for Search and Rescue Missions.
In 2018 6TH INTERNATIONAL ELECTRICAL ENGINEERING CONGRESS (IEECON). In series: International Electrical Engineering Congress #??. IEEE. ISBN: 978-1-5386-2317-6.
DOI: 10.1109/IEECON.2018.8712230.
Note: Funding Agencies|Swedish Research Council CADICS; ELLIIT network organization for Information and Communication Technology; Swedish Foundation for Strategic Research [RIT 15-0097]

Due to the maturity of technological development, widespread use of Unmanned Aerial Vehicles (UAVs) is becoming prevalent in the civil and commercial sectors. One promising area of application is in emergency rescue support. As recently seen in a number of natural catastrophes such as the hurricanes in Texas, Florida and Puerto Rico, major communication and electrical infrastructure is knocked out, leading to an inability to communicate between the victims and rescuers on the ground as well as between rescuers themselves. This paper studies the feasibility of using heterogeneous teams of UAVs to rapidly deliver and establish ad hoc communication networks in operational environments through autonomous in-air delivery of CommKits that serve as nodes in local ad hoc networks. Hardware and software infrastructures for autonomous CommKit delivery in addition to CommKit specification and construction is considered. The results of initial evaluation of two design alternatives for CommKits are presented based on more than 25 real flight tests in different weather conditions using a commercial small-scale UAV platform.

[141] Full text  Mikael Nilsson, Jonas Kvarnström and Patrick Doherty. 2018.
Planning with Temporal Uncertainty, Resources and Non-Linear Control Parameters.
In Mathijs de Weerdt, Sven Koenig, Gabriele Röger, Matthijs Spaan, editors, Proceedings of the Twenty-Eighth International Conference on Automated Planning and Scheduling (ICAPS), pages 180–189. In series: International Conference on Automated Planning and Scheduling #??. AAAI Press. ISBN: 978-1-57735-797-1.
AAAI Digital Library: http://www.aaai.org/Library/ICAPS/icaps1...

We consider a general and industrially motivated class of planning problems involving a combination of requirements that can be essential to autonomous robotic systems planning to act in the real world: Support for temporal uncertainty where nature determines the eventual duration of an action, resource consumption with a non-linear relationship to durations, and the need to select appropriate values for control parameters that affect time requirements and resource usage. To this end, an existing planner is extended with support for Simple Temporal Networks with Uncertainty, Timed Initial Literals, and temporal coverage goals. Control parameters are lifted from the main combinatorial planning problem into a constraint satisfaction problem that connects them to resource usage. Constraint processing is then integrated and interleaved with verification of temporal feasibility, using projections for partial temporal awareness in the constraint solver.

2017
[140] Full text  Mariusz Wzorek, Cyrille Berger and Patrick Doherty. 2017.
A Framework for Safe Navigation of Unmanned Aerial Vehicles in Unknown Environments.
In 2017 25TH INTERNATIONAL CONFERENCE ON SYSTEMS ENGINEERING (ICSENG), pages 11–20. IEEE. ISBN: 978-1-5386-0610-0.
DOI: 10.1109/ICSEng.2017.58.
Note: Funding Agencies|Swedish Research Council (VR) Linnaeus Center CADICS; ELLIIT network organization for Information and Communication Technology; Swedish Foundation for Strategic Research [RIT 15-0097]

This paper presents a software framework which combines reactive collision avoidance control approach with path planning techniques for the purpose of safe navigation of multiple Unmanned Aerial Vehicles (UAVs) operating in unknown environments. The system proposed leverages advantages of using a fast local sense-and-react type control which guarantees real-time execution with computationally demanding path planning algorithms which generate globally optimal plans. A number of probabilistic path planning algorithms based on Probabilistic Roadmaps and Rapidly-Exploring Random Trees have been integrated. Additionally, the system uses a reactive controller based on Optimal Reciprocal Collision Avoidance (ORCA) for path execution and fast sense-and-avoid behavior. During the mission execution a 3D map representation of the environment is build incrementally and used for path planning. A prototype implementation on a small scale quad-rotor platform has been developed. The UAV used in the experiments was equipped with a structured-light depth sensor to obtain information about the environment in form of occupancy grid map. The system has been tested in a number of simulated missions as well as in real flights and the results of the evaluations are presented.

[139] Full text  Piotr Rudol and Patrick Doherty. 2017.
Bridging Reactive and Control Architectural Layers for Cooperative Missions Using VTOL Platforms.
In 2017 25TH INTERNATIONAL CONFERENCE ON SYSTEMS ENGINEERING (ICSENG), pages 21–32. IEEE. ISBN: 978-1-5386-0610-0.
DOI: 10.1109/ICSEng.2017.59.
Note: Funding Agencies|Swedish Research Council (VR) Linnaeus Center CADICS; ELLIIT network organization for Information and Communication Technology; Swedish Foundation for Strategic Research (SymbiKcloud Project)

In this paper we address the issue of connecting abstract task definitions at a mission level with control functionalities for the purpose of performing autonomous robotic missions using multiple heterogenous platforms. The heterogeneity is handled by the use of a common vocabulary which consists of parametrized tasks such as fly-to, take-off, scan-area, or land. Each of the platforms participating in a mission supports a subset of the tasks by providing their platform-specific implementations. This paper presents a detailed description of an approach for implementing such platform-specific tasks. It is achieved using a flight-command based interface with setpoint generation abstraction layer for vertical take-off and landing platforms. We show that by using this highly expressive and easily parametrizable way of specifying and executing flight behaviors it is straightforward to implement a wide range of tasks. We describe the method in the context of a previously described robotics architecture which includes mission delegation and execution system based on a task specification language. We present results of an experimental flight using the proposed method.

[138] Timo Hinzmann, Thomas Stastny, Gianpaolo Conte, Patrick Doherty, Piotr Rudol, Mariusz Wzorek, Enric Galceran, Roland Siegwart and Igor Gilitschenski. 2017.
Collaborative 3D Reconstruction Using Heterogeneous UAVs: System and Experiments.
In 2016 INTERNATIONAL SYMPOSIUM ON EXPERIMENTAL ROBOTICS, pages 43–56. In series: Springer Proceedings in Advanced Robotics #??. SPRINGER INTERNATIONAL PUBLISHING AG. ISBN: 978-3-319-50115-4, 978-3-319-50114-7.
DOI: 10.1007/978-3-319-50115-4_5.
Note: Funding Agencies|European Commissions Seventh Framework Programme (FP7) [285417, 600958]

This paper demonstrates how a heterogeneous fleet of unmanned aerial vehicles (UAVs) can support human operators in search and rescue (SaR) scenarios. We describe a fully autonomous delegation framework that interprets the top-level commands of the rescue team and converts them into actions of the UAVs. In particular, the UAVs are requested to autonomously scan a search area and to provide the operator with a consistent georeferenced 3D reconstruction of the environment to increase the environmental awareness and to support critical decision-making. The mission is executed based on the individual platform and sensor capabilities of rotary-and fixed-wing UAVs (RW-UAV and FW-UAV respectively): With the aid of an optical camera, the FW-UAV can generate a sparse point-cloud of a large area in a short amount of time. A LiDAR mounted on the autonomous helicopter is used to refine the visual point-cloud by generating denser point-clouds of specific areas of interest. In this context, we evaluate the performance of point-cloud registration methods to align two maps that were obtained by different sensors. In our validation, we compare classical point-cloud alignment methods to a novel probabilistic data association approach that specifically takes the individual point-cloud densities into consideration.

[137] Full text  Mariusz Wzorek, Piotr Rudol, Gianpaolo Conte and Patrick Doherty. 2017.
LinkBoard: Advanced Flight Control System for Micro Unmanned Aerial Vehicles.
In 2017 2ND INTERNATIONAL CONFERENCE ON CONTROL AND ROBOTICS ENGINEERING (ICCRE2017). IEEE. ISBN: 978-1-5090-3774-2.
DOI: 10.1109/ICCRE.2017.7935051.
Note: Funding Agencies|Swedish Research Council (VR) Linnaeus Center CADICS; ELLIIT network organization for Information and Communication Technology; Swedish Foundation for Strategic Research [RIT 15-0097]

This paper presents the design and development of the LinkBoard, an advanced flight control system for micro Unmanned Aerial Vehicles (UAVs). Both hardware and software architectures are presented. The LinkBoard includes four processing units and a full inertial measurement unit. In the basic configuration, the software architecture includes a fully configurable set of control modes and sensor fusion algorithms for autonomous UAV operation. The system proposed allows for easy integration with new platforms, additional external sensors and a flexibility to trade off computational power, weight and power consumption. Due to the available onboard computational power, it has been used for computationally demanding applications such as the implementation of an autonomous indoor vision-based navigation system with all computations performed onboard. The autopilot has been manufactured and deployed on multiple UAVs. Examples of UAV systems built with the LinkBoard and their applications are presented, as well as an in-flight experimental performance evaluation of a newly developed attitude estimation filter.

[136] Full text  Olov Andersson, Mariusz Wzorek and Patrick Doherty. 2017.
Deep Learning Quadcopter Control via Risk-Aware Active Learning.
In Satinder Singh and Shaul Markovitch, editors, Proceedings of The Thirty-first AAAI Conference on Artificial Intelligence (AAAI), pages 3812–3818. In series: Proceedings of the AAAI Conference on Artificial Intelligence #5. AAAI Press. ISBN: 978-1-57735-784-1.

Modern optimization-based approaches to control increasingly allow automatic generation of complex behavior from only a model and an objective. Recent years has seen growing interest in fast solvers to also allow real-time operation on robots, but the computational cost of such trajectory optimization remains prohibitive for many applications. In this paper we examine a novel deep neural network approximation and validate it on a safe navigation problem with a real nano-quadcopter. As the risk of costly failures is a major concern with real robots, we propose a risk-aware resampling technique. Contrary to prior work this active learning approach is easy to use with existing solvers for trajectory optimization, as well as deep learning. We demonstrate the efficacy of the approach on a difficult collision avoidance problem with non-cooperative moving obstacles. Our findings indicate that the resulting neural network approximations are least 50 times faster than the trajectory optimizer while still satisfying the safety requirements. We demonstrate the potential of the approach by implementing a synthesized deep neural network policy on the nano-quadcopter microcontroller.

2016
[135] Gustav Häger, Goutam Bhat, Martin Danelljan, Fahad Shahbaz Khan, Michael Felsberg, Piotr Rudol and Patrick Doherty. 2016.
Combining Visual Tracking and Person Detection for Long Term Tracking on a UAV.
In Proceedings of the 12th International Symposium on Advances in Visual Computing. In series: Lecture Notes in Computer Science #??. Springer. ISBN: 978-3-319-50834-4, 978-3-319-50835-1.
DOI: 10.1007/978-3-319-50835-1_50.
fulltext:postprint: http://liu.diva-portal.org/smash/get/div...

Visual object tracking performance has improved significantly in recent years. Most trackers are based on either of two paradigms: online learning of an appearance model or the use of a pre-trained object detector. Methods based on online learning provide high accuracy, but are prone to model drift. The model drift occurs when the tracker fails to correctly estimate the tracked object’s position. Methods based on a detector on the other hand typically have good long-term robustness, but reduced accuracy compared to online methods.Despite the complementarity of the aforementioned approaches, the problem of fusing them into a single framework is largely unexplored. In this paper, we propose a novel fusion between an online tracker and a pre-trained detector for tracking humans from a UAV. The system operates at real-time on a UAV platform. In addition we present a novel dataset for long-term tracking in a UAV setting, that includes scenarios that are typically not well represented in standard visual tracking datasets.

[134] Patrick Doherty and Andrzej Szalas. 2016.
An Entailment Procedure for Kleene Answer Set Programs.
In Sombattheera C., Stolzenburg F., Lin F., Nayak A., editors, Multi-disciplinary Trends in Artificial Intelligence. MIWAI 2016., pages 24–37. In series: Lecture Notes in Computer Science #10053. Springer. ISBN: 978-3-319-49396-1, 978-3-319-49397-8.
DOI: 10.1007/978-3-319-49397-8_3.

Classical Answer Set Programming is a widely known knowledge representation framework based on the logic programming paradigm that has been extensively studied in the past decades. Semantic theories for classical answer sets are implicitly three-valued in nature, yet with few exceptions, computing classical answer sets is based on translations into classical logic and the use of SAT solving techniques. In this paper, we introduce a variation of Kleene three-valued logic with strong connectives, R3\" role=\"presentation\">R3, and then provide a sound and complete proof procedure for R3\" role=\"presentation\">R3 based on the use of signed tableaux. We then define a restriction on the syntax of R3\" role=\"presentation\">R3 to characterize Kleene ASPs. Strongly-supported models, which are a subset of R3\" role=\"presentation\">R3 models are then defined to characterize the semantics of Kleene ASPs. A filtering technique on tableaux for R3\" role=\"presentation\">R3 is then introduced which provides a sound and complete tableau-based proof technique for Kleene ASPs. We then show a translation and semantic correspondence between Classical ASPs and Kleene ASPs, where answer sets for normal classical ASPs are equivalent to strongly-supported models. This implies that the proof technique introduced can be used for classical normal ASPs as well as Kleene ASPs. The relation between non-normal classical and Kleene ASPs is also considered.

[133] Full text  Patrick Doherty, Jonas Kvarnström and Andrzej Szalas. 2016.
Iteratively-Supported Formulas and Strongly Supported Models for Kleene Answer Set Programs.
In Michael, Loizos; Kakas, Antonis, editors, Logics in Artificial Intelligence: 15th European Conference, JELIA 2016, Larnaca, Cyprus, November 9-11, 2016, Proceedings, pages 536–542. In series: Lecture Notes in Computer Science #10021. Springer Publishing Company. ISBN: 978-3-319-48757-1, 978-3-319-48758-8.
DOI: 10.1007/978-3-319-48758-8_36.

In this extended abstract, we discuss the use of iteratively-supported formulas (ISFs) as a basis for computing strongly-supported models for Kleene Answer Set Programs (ASPK). ASPK programs have a syntax identical to classical ASP programs. The semantics of ASPK programs is based on the use of Kleene three-valued logic and strongly-supported models. For normal ASPK programs, their strongly supported models are identical to classical answer sets using stable model semantics. For disjunctive ASPK programs, the semantics weakens the minimality assumption resulting in a classical interpretation for disjunction. We use ISFs to characterize strongly-supported models and show that they are polynomially bounded.

[132] Full text  Piotr Rudol and Patrick Doherty. 2016.
Bridging the mission-control gap: A flight command layer for mediating flight behaviours and continuous control.
In 2016 IEEE International Symposium on Safety, Security, and Rescue Robotics (SSRR), pages 304–311. In series: 2016 IEEE INTERNATIONAL SYMPOSIUM ON SAFETY, SECURITY, AND RESCUE ROBOTICS (SSRR) #??. Institute of Electrical and Electronics Engineers (IEEE). ISBN: 9781509043491, 9781509043507.
DOI: 10.1109/SSRR.2016.7784320.

The use of UAVs, in particular, micro VTOL UAVs, is becoming prevalent in emergency rescue and security applications, among others. In these applications, the platforms are tightly coupled to the human users and these applications require great flexibility in the interaction between the platforms and such users. During operation, one continually switches between manual, semi-autonomous and autonomous operation, often re-parameterising, breaking in, pausing, and resuming missions. One is in continual need of modifying existing elementary actions and behaviours such as FlyTo and TrackObject, and seamlessly switching between such operations. This paper proposes a flight command and setpoint abstraction layer that serves as an interface between continuous control and higher level elementary flight actions and behaviours. Introduction of such a layer into an architecture offers a versatile and flexible means of defining flight behaviours and dynamically parameterising them in the field, in particular where human users are involved. The system proposed is implemented in prototype and the paper provides experimental validation of the use and need for such abstractions in system architectures.

[131] Full text  Cyrille Berger, Mariusz Wzorek, Jonas Kvarnström, Gianpaolo Conte, Patrick Doherty and Alexander Eriksson. 2016.
Area Coverage with Heterogeneous UAVs using Scan Patterns.
In 2016 IEEE International Symposium on Safety, Security, and Rescue Robotics (SSRR): proceedings. In series: 2016 IEEE INTERNATIONAL SYMPOSIUM ON SAFETY, SECURITY, AND RESCUE ROBOTICS (SSRR) #??. IEEE Robotics and Automation Society. ISBN: 978-1-5090-4349-1.
DOI: 10.1109/SSRR.2016.7784325.
fulltext:postprint: http://liu.diva-portal.org/smash/get/div...

In this paper we consider a problem of scanningan outdoor area with a team of heterogeneous Unmanned AirVehicles (UAVs) equipped with different sensors (e.g. LIDARs).Depending on the availability of the UAV platforms and themission requirements there is a need to either minimise thetotal mission time or to maximise certain properties of thescan output, such as the point cloud density. The key challengeis to divide the scanning task among UAVs while taking intoaccount the differences in capabilities between platforms andsensors. Additionally, the system should be able to ensure thatconstraints such as limit on the flight time are not violated.We present an approach that uses an optimisation techniqueto find a solution by dividing the area between platforms,generating efficient scan trajectories and selecting flight andscanning parameters, such as velocity and flight altitude. Thismethod has been extensively tested on a large set of randomlygenerated scanning missions covering a wide range of realisticscenarios as well as in real flights.

[130] Jose Renato Garcia Braga, Gianpaolo Conte, Patrick Doherty, Haroldo Fraga Campos Velho and Elcio Hideiti Shiguemori. 2016.
An Image Matching System for Autonomous UAV Navigation Based on Neural Network.
In 14th International Conference on Control, Automation, Robotics and Vision (ICARCV 2016). In series: International Conference on Control Automation Robotics and Vision #??. ISBN: 978-1-5090-3549-6, 978-1-5090-3550-2.
DOI: 10.1109/ICARCV.2016.7838775.
Note: Funding agencies:This work was carried out with support from CNPq - National Counsel of Technological and Scientific Development - Brazil. This work is partially supported by the Swedish Research Council (VR) Linnaeus Center CADICS, ELLIIT, and the Swedish Foundation for Strategic Research (CUAS Project, SymbiKCloud Project).

This paper proposes an image matching system using aerial images, captured in flight time, and aerial geo-referenced images to estimate the Unmanned Aerial Vehicle (UAV) position in a situation of Global Navigation Satellite System (GNSS) failure. The image matching system is based on edge detection in the aerial and geo-referenced image and posterior automatic image registration of these edge-images (position estimation of UAV). The edge detection process is performed by an Artificial Neural Network (ANN), with an optimal architecture. A comparison with Sobel and Canny edge extraction filters is also provided. The automatic image registration is obtained by a cross-correlation process. The ANN optimal architecture is set by the Multiple Particle Collision Algorithm (MPCA). The image matching system was implemented in a low cost/consumption portable computer. The image matching system has been tested on real flight-test data and encouraging results have been obtained. Results using real flight-test data will be presented.

[129] Full text  Jose Renato Garcia Braga, Gianpaolo Conte, Patrick Doherty, Haroldo Fraga Campos Velho and Elcio Hideiti Shiguemori. 2016.
Use of Artificial Neural Networks for Automatic Categorical Change Detection in Satellite Imagery.
In Proceedings of the 4th Conference of Computational Interdisciplinary Sciences (CCIS 2016). Pan American Association of Computational Interdisciplinary.

[128] Full text  Patrick Doherty, Jonas Kvarnström, Piotr Rudol, Mariusz Wzorek, Gianpaolo Conte, Cyrille Berger, Timo Hinzmann and Thomas Stastny. 2016.
A Collaborative Framework for 3D Mapping using Unmanned Aerial Vehicles.
In Baldoni, M., Chopra, A.K., Son, T.C., Hirayama, K., Torroni, P., editors, PRIMA 2016: Principles and Practice of Multi-Agent Systems, pages 110–130. In series: Lecture Notes in Computer Science #9862. Springer Publishing Company. ISBN: 978-3-319-44831-2.
DOI: 10.1007/978-3-319-44832-9_7.
Note: Accepted for publication.

This paper describes an overview of a generic framework for collaboration among humans and multiple heterogeneous robotic systems based on the use of a formal characterization of delegation as a speech act. The system used contains a complex set of integrated software modules that include delegation managers for each platform, a task specification language for characterizing distributed tasks, a task planner, a multi-agent scan trajectory generation and region partitioning module, and a system infrastructure used to distributively instantiate any number of robotic systems and user interfaces in a collaborative team. The application focusses on 3D reconstruction in alpine environments intended to be used by alpine rescue teams. Two complex UAV systems used in the experiments are described. A fully autonomous collaborative mission executed in the Italian Alps using the framework is also described.

[127] Full text  Olov Andersson, Mariusz Wzorek, Piotr Rudol and Patrick Doherty. 2016.
Model-Predictive Control with Stochastic Collision Avoidance using Bayesian Policy Optimization.
In IEEE International Conference on Robotics and Automation (ICRA), 2016, pages 4597–4604. In series: Proceedings of IEEE International Conference on Robotics and Automation #??. Institute of Electrical and Electronics Engineers (IEEE).
DOI: 10.1109/ICRA.2016.7487661.

Robots are increasingly expected to move out of the controlled environment of research labs and into populated streets and workplaces. Collision avoidance in such cluttered and dynamic environments is of increasing importance as robots gain more autonomy. However, efficient avoidance is fundamentally difficult since computing safe trajectories may require considering both dynamics and uncertainty. While heuristics are often used in practice, we take a holistic stochastic trajectory optimization perspective that merges both collision avoidance and control. We examine dynamic obstacles moving without prior coordination, like pedestrians or vehicles. We find that common stochastic simplifications lead to poor approximations when obstacle behavior is difficult to predict. We instead compute efficient approximations by drawing upon techniques from machine learning. We propose to combine policy search with model-predictive control. This allows us to use recent fast constrained model-predictive control solvers, while gaining the stochastic properties of policy-based methods. We exploit recent advances in Bayesian optimization to efficiently solve the resulting probabilistically-constrained policy optimization problems. Finally, we present a real-time implementation of an obstacle avoiding controller for a quadcopter. We demonstrate the results in simulation as well as with real flight experiments.

2015
[126] Full text  Mikael Nilsson, Jonas Kvarnström and Patrick Doherty. 2015.
Revisiting Classical Dynamic Controllability: A Tighter Complexity Analysis.
In Béatrice Duval; Jaap van den Herik; Stephane Loiseau; Joaquim Filipe, editor, Agents and Artificial Intelligence: 6th International Conference, ICAART 2014, Angers, France, March 6–8, 2014, Revised Selected Papers, pages 243–261. In series: Lecture Notes in Computer Science #8946. Springer. ISBN: 978-3-319-25209-4, 978-3-319-25210-0.
DOI: 10.1007/978-3-319-25210-0_15.

Simple Temporal Networks with Uncertainty (STNUs) allow the representation of temporal problems where some durations are uncontrollable (determined by nature), as is often the case for actions in planning. It is essential to verify that such networks are dynamically controllable (DC) -- executable regardless of the outcomes of uncontrollable durations -- and to convert them to an executable form. We use insights from incremental DC verification algorithms to re-analyze the original, classical, verification algorithm. This algorithm is the entry level algorithm for DC verification, based on a less complex and more intuitive theory than subsequent algorithms. We show that with a small modification the algorithm is transformed from pseudo-polynomial to O(n<sup>4</sup>) which makes it still useful. We also discuss a change reducing the amount of work performed by the algorithm.

[125] Full text  Martin Danelljan, Fahad Shahbaz Khan, Michael Felsberg, Karl Granström, Fredrik Heintz, Piotr Rudol, Mariusz Wzorek, Jonas Kvarnström and Patrick Doherty. 2015.
A Low-Level Active Vision Framework for Collaborative Unmanned Aircraft Systems.
In Lourdes Agapito, Michael M. Bronstein and Carsten Rother, editors, COMPUTER VISION - ECCV 2014 WORKSHOPS, PT I, pages 223–237. In series: Lecture Notes in Computer Science #8925. Springer Publishing Company. ISBN: 978-3-319-16177-8, 978-3-319-16178-5.
DOI: 10.1007/978-3-319-16178-5_15.
fulltext:postprint: http://liu.diva-portal.org/smash/get/div...

Micro unmanned aerial vehicles are becoming increasingly interesting for aiding and collaborating with human agents in myriads of applications, but in particular they are useful for monitoring inaccessible or dangerous areas. In order to interact with and monitor humans, these systems need robust and real-time computer vision subsystems that allow to detect and follow persons.In this work, we propose a low-level active vision framework to accomplish these challenging tasks. Based on the LinkQuad platform, we present a system study that implements the detection and tracking of people under fully autonomous flight conditions, keeping the vehicle within a certain distance of a person. The framework integrates state-of-the-art methods from visual detection and tracking, Bayesian filtering, and AI-based control. The results from our experiments clearly suggest that the proposed framework performs real-time detection and tracking of persons in complex scenarios

[124] Full text  Olov Andersson, Fredrik Heintz and Patrick Doherty. 2015.
Model-Based Reinforcement Learning in Continuous Environments Using Real-Time Constrained Optimization.
In Blai Bonet and Sven Koenig, editors, Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence (AAAI), pages 2497–2503. AAAI Press. ISBN: 978-1-57735-698-1.
fulltext:print: http://liu.diva-portal.org/smash/get/div...

Reinforcement learning for robot control tasks in continuous environments is a challenging problem due to the dimensionality of the state and action spaces, time and resource costs for learning with a real robot as well as constraints imposed for its safe operation. In this paper we propose a model-based reinforcement learning approach for continuous environments with constraints. The approach combines model-based reinforcement learning with recent advances in approximate optimal control. This results in a bounded-rationality agent that makes decisions in real-time by efficiently solving a sequence of constrained optimization problems on learned sparse Gaussian process models. Such a combination has several advantages. No high-dimensional policy needs to be computed or stored while the learning problem often reduces to a set of lower-dimensional models of the dynamics. In addition, hard constraints can easily be included and objectives can also be changed in real-time to allow for multiple or dynamic tasks. The efficacy of the approach is demonstrated on both an extended cart pole domain and a challenging quadcopter navigation task using real data.

2014
[123] Oleg Burdakov, Patrick Doherty and Jonas Kvarnström. 2014.
Local Search for Hop-constrained Directed Steiner Tree Problem with Application to UAV-based Multi-target Surveillance.
In Butenko, S., Pasiliao, E.L., Shylo, V., editors, Examining Robustness and Vulnerability of Networked Systems, pages 26–50. In series: NATO Science for Peace and Security Series - D: Information and Communication Security #37. IOS Press. ISBN: 978-1-61499-390-2, 978-1-61499-391-9.
DOI: 10.3233/978-1-61499-391-9-26.
Find book in another country/Hitta boken i ett annat land: http://www.worldcat.org/search?q=978-1-6...
fulltext:postprint: http://liu.diva-portal.org/smash/get/div...

We consider the directed Steiner tree problem (DSTP) with a constraint on the total number of arcs (hops) in the tree. This problem is known to be NP-hard, and therefore, only heuristics can be applied in the case of its large-scale instances.For the hop-constrained DSTP, we propose local search strategies aimed at improving any heuristically produced initial Steiner tree. They are based on solving a sequence of hop-constrained shortest path problems for which we have recently developed efficient label correcting algorithms.The presented approach is applied to finding suitable 3D locations where unmanned aerial vehicles (UAVs) can be placed to relay information gathered in multi-target monitoring and surveillance. The efficiency of our algorithms is illustrated by results of numerical experiments involving problem instances with up to 40 000 nodes and up to 20 million arcs.

[122] Full text  Mikael Nilsson, Jonas Kvarnström and Patrick Doherty. 2014.
Incremental Dynamic Controllability in Cubic Worst-Case Time.
In Cesta, A; Combi, C; Laroussinie, F, editors, Proceedings of the 21st International Symposium on Temporal Representation and Reasoning (TIME), pages 17–26. In series: International Workshop on Temporal Representation and Reasoning. Proceedings #??. IEEE Computer Society Digital Library. ISBN: 978-1-4799-4227-5.
DOI: 10.1109/TIME.2014.13.

It is generally hard to predict the exact duration of an action. The uncertainty in the duration is often modeled in temporal planning by the use of upper bounds on durations, with the assumption that if an action happens to be executed more quickly, the plan will still succeed. However, this assumption is often false: If we finish cooking too early, the dinner will be cold before everyone is ready to eat. Simple Temporal Problems with Uncertainty (STPUs) allow us to model such situations. An STPU-based planner must verify that the plans it generates are executable, captured by the property of dynamic controllability. The EfficientIDC (EIDC) algorithm can do this incrementally during planning, with an amortized complexity per step of $O(n^3)$ but a worst-case complexity per step of $O(n^4)$. In this paper we show that the worst-case run-time of EIDC does occur, leading to repeated reprocessing of nodes in the STPU while verifying the dynamic controllability property. We present a new version of the algorithm, called EIDC2, which through optimal ordering of nodes avoids any need for reprocessing. This gives EIDC2 a strictly lower worst-case run-time, making it the fastest known algorithm for incrementally verifying dynamic controllability of STPUs.

[121] Mikael Nilsson, Jonas Kvarnström and Patrick Doherty. 2014.
Efficient IDC: A Faster Incremental Dynamic Controllability Algorithm.
In Proceedings of the 24th International Conference on Automated Planning and Scheduling (ICAPS), pages 199–207. AAAI Press. ISBN: 978-1-57735-660-8.

Simple Temporal Networks with Uncertainty (STNUs) allow the representation of temporal problems where some durations are uncontrollable (determined by nature), as is often the case for actions in planning. It is essential to verify that such networks are dynamically controllable (DC) – executable regardless of the outcomes of uncontrollable durations – and to convert them to an executable form. We use insights from incremental DC verification algorithms to re-analyze the original verification algorithm. This algorithm, thought to be pseudo-polynomial and subsumed by an O(n5) algorithm and later an O(n4) algorithm, is in fact O(n4) given a small modification. This makes the algorithm attractive once again, given its basis in a less complex and more intuitive theory. Finally, we discuss a change reducing the amount of work performed by the algorithm.

[120] Full text  Mikael Nilsson, Jonas Kvarnström and Patrick Doherty. 2014.
Classical Dynamic Controllability Revisited: A Tighter Bound on the Classical Algorithm.
In Proceedings of the 6th International Conference on Agents and Artificial Intelligence (ICAART), pages 130–141. ISBN: 978-989-758-015-4.
DOI: 10.5220/0004815801300141.

Simple Temporal Networks with Uncertainty (STNUs) allow the representation of temporal problems wheresome durations are uncontrollable (determined by nature), as is often the case for actions in planning. It is essentialto verify that such networks are dynamically controllable (DC) – executable regardless of the outcomesof uncontrollable durations – and to convert them to an executable form. We use insights from incrementalDC verification algorithms to re-analyze the original verification algorithm. This algorithm, thought to bepseudo-polynomial and subsumed by an O(n<sup>5</sup>) algorithm and later an O(n<sup>4</sup>) algorithm, is in fact O(n<sup>4</sup>) givena small modification. This makes the algorithm attractive once again, given its basis in a less complex andmore intuitive theory. Finally, we discuss a change reducing the amount of work performed by the algorithm.

2013
[119] Full text  Patrick Doherty, Fredrik Heintz and Jonas Kvarnström. 2013.
Robotics, Temporal Logic and Stream Reasoning.
In Proceedings of Logic for Programming Artificial Intelligence and Reasoning (LPAR), 2013.

[118] Full text  Gianpaolo Conte, Alexander Kleiner, Piotr Rudol, Karol Korwel, Mariusz Wzorek and Patrick Doherty. 2013.
Performance evaluation of a light weight multi-echo LIDAR for unmanned rotorcraft applications.
In International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XL-1/W2. In series: International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences #??. Copernicus Gesellschaft MBH.

The paper presents a light-weight and low-cost airborne terrain mapping system. The developed Airborne LiDAR Scanner (ALS) sys- tem consists of a high-precision GNSS receiver, an inertial measurement unit and a magnetic compass which are used to complement a LiDAR sensor in order to compute the terrain model. Evaluation of the accuracy of the generated 3D model is presented. Additionally, a comparison is provided between the terrain model generated from the developed ALS system and a model generated using a commer- cial photogrammetric software. Finally, the multi-echo capability of the used LiDAR sensor is evaluated in areas covered with dense vegetation. The ALS system and camera systems were mounted on-board an industrial unmanned helicopter of around 100 kilograms maximum take-off weight. Presented results are based on real flight-test data.

[117] Full text  Håkan Warnquist, Jonas Kvarnström and Patrick Doherty. 2013.
Exploiting Fully Observable and Deterministic Structures in Goal POMDPs.
In Daniel Borrajo, Subbarao Kambhampati, Angelo Oddi, Simone Fratini, editors, Proceedings of the 23rd International Conference on Automated Planning and Scheduling (ICAPS), pages 242–250. AAAI Press. ISBN: 978-1-57735-609-7.
Link to full text: http://www.aaai.org/ocs/index.php/ICAPS/...

When parts of the states in a goal POMDP are fully observable and some actions are deterministic it is possibleto take advantage of these properties to efficiently generate approximate solutions. Actions that deterministically affect the fully observable component of the world state can be abstracted away and combined into macro actions, permitting a planner to converge more quickly. This processing can be separated from the main search procedure, allowing us to leverage existing POMDP solvers. Theoretical results show how a POMDP can be analyzed to identify the exploitable properties and formal guarantees are provided showing that the use of macro actions preserves solvability. The efficiency of the method is demonstrated with examples when used in combination with existing POMDP solvers.

[116] Full text  Mikael Nilsson, Jonas Kvarnström and Patrick Doherty. 2013.
Incremental Dynamic Controllability Revisited.
In Proceedings of the 23rd International Conference on Automated Planning and Scheduling (ICAPS). AAAI Press. ISBN: 978-1-57735-609-7.

Simple Temporal Networks with Uncertainty (STNUs) allow the representation of temporal problems where some durations are determined by nature, as is often the case for actions in planning. As such networks are generated it is essential to verify that they are dynamically controllable – executable regardless of the outcomes of uncontrollable durations – and to convert them to a dispatchable form. The previously published FastIDC algorithm achieves this incrementally and can therefore be used efficiently during plan construction. In this paper we show that FastIDC is not sound when new constraints are added, sometimes labeling networks as dynamically controllable when they are not. We analyze the algorithm, pinpoint the cause, and show how the algorithm can be modified to correctly detect uncontrollable networks.

2012
[115] Patrick Doherty, Fredrik Heintz and David Landén. 2012.
A Distributed Task Specification Language for Mixed-Initiative Delegation.
In Nirmit Desai, Alan Liu, Michael Winikoff, editors, Principles and Practice of Multi-Agent Systems: 13th International Conference, PRIMA 2010, Kolkata, India, November 12-15, 2010, Revised Selected Papers, pages 42–57. In series: Lecture Notes in Computer Science #7057. Springer Berlin/Heidelberg. ISBN: 978-3-642-25919-7, 978-3-642-25920-3.
DOI: 10.1007/978-3-642-25920-3_4.

In the next decades, practically viable robotic/agent systems are going to be mixed-initiative in nature. Humans will request help from such systems and such systems will request help from humans in achieving the complex mission tasks required. Pragmatically, one requires a distributed task specification language to define tasks and a suitable data structure which satisfies the specification and can be used flexibly by collaborative multi-agent/robotic systems. This paper defines such a task specification language and an abstract data structure called Task Specification Trees which has many of the requisite properties required for mixed-initiative problem solving and adjustable autonomy in a distributed context. A prototype system has been implemented for this delegation framework and has been used practically with collaborative unmanned aircraft systems.

[114] David Landén, Fredrik Heintz and Patrick Doherty. 2012.
Complex Task Allocation in Mixed-Initiative Delegation: A UAV Case Study.
In Nirmit Desai, Alan Liu, Michael Winikoff, editors, Principles and Practice of Multi-Agent Systems: 13th International Conference, PRIMA 2010, Kolkata, India, November 12-15, 2010, Revised Selected Papers, pages 288–303. In series: Lecture Notes in Computer Science #7057. Springer Berlin/Heidelberg. ISBN: 978-3-642-25919-7, 978-3-642-25920-3.
DOI: 10.1007/978-3-642-25920-3_20.

Unmanned aircraft systems (UASs) are now becoming technologically mature enough to be integrated into civil society. An essential issue is principled mixed-initiative interaction between UASs and human operators. Two central problems are to specify the structure and requirements of complex tasks and to assign platforms to these tasks. We have previously proposed Task Specification Trees (TSTs) as a highly expressive specification language for complex multi-agent tasks that supports mixed-initiative delegation and adjustable autonomy. The main contribution of this paper is a sound and complete distributed heuristic search algorithm for allocating the individual tasks in a TST to platforms. The allocation also instantiates the parameters of the tasks such that all the constraints of the TST are satisfied. Constraints are used to model dependencies between tasks, resource usage as well as temporal and spatial requirements on complex tasks. Finally, we discuss a concrete case study with a team of unmanned aerial vehicles assisting in a challenging emergency situation.

[113] L. Marconi, C. Melchiorri, M. Beetz, D. Pangercic, R. Siegwart, S. Leutenegger, R. Carloni, S. Stramigioli, H. Bruyninckx, Patrick Doherty, Alexander Kleiner, V. Lippiello, A. Finzi, B. Siciliano, A. Sala and N. Tomatis. 2012.
The SHERPA project: Smart collaboration between humans and ground-aerial robots for improving rescuing activities in alpine environments.
In Proc. of the IEEE Int. Workshop on Safety, Security and Rescue Robotics (SSRR), pages 1–4. IEEE. ISBN: 978-1-4799-0164-7, 978-1-4799-0163-0, 978-1-4799-0165-4.
DOI: 10.1109/SSRR.2012.6523905.

The goal of the paper is to present the foreseen research activity of the European project “SHERPA” whose activities will start officially on February 1th 2013. The goal of SHERPA is to develop a mixed ground and aerial robotic platform to support search and rescue activities in a real-world hostile environment, like the alpine scenario that is specifically targeted in the project. Looking into the technological platform and the alpine rescuing scenario, we plan to address a number of research topics about cognition and control. What makes the project potentially very rich from a scientific viewpoint is the heterogeneity and the capabilities to be owned by the different actors of the SHERPA system: the human rescuer is the “busy genius”, working in team with the ground vehicle, as the “intelligent donkey”, and with the aerial platforms, i.e. the “trained wasps” and “patrolling hawks”. Indeed, the research activity focuses on how the “busy genius” and the “SHERPA animals” interact and collaborate with each other, with their own features and capabilities, toward the achievement of a common goal.

[112] Full text  Patrick Doherty and Fredrik Heintz. 2012.
Delegation-Based Collaboration.
In Proceedings of the 5th International Conference on Cognitive Systems (CogSys).

[111] Full text  Patrick Doherty, Jonas Kvarnström and Andrzej Szalas. 2012.
Temporal Composite Actions with Constraints.
In Proceedings of the 13th International Conference on Principles of Knowledge Representation and Reasoning (KR), pages 478–488. AAAI Press. ISBN: 978-1-57735-560-1, 978-1-57735-561-8.
Link: http://www.aaai.org/ocs/index.php/KR/KR1...

Complex mission or task specification languages play a fundamentally important role in human/robotic interaction. In realistic scenarios such as emergency response, specifying temporal, resource and other constraints on a mission is an essential component due to the dynamic and contingent nature of the operational environments. It is also desirable that in addition to having a formal semantics, the language should be sufficiently expressive, pragmatic and abstract. The main goal of this paper is to propose a mission specification language that meets these requirements. It is based on extending both the syntax and semantics of a well-established formalism for reasoning about action and change, Temporal Action Logic (TAL), in order to represent temporal composite actions with constraints. Fixpoints are required to specify loops and recursion in the extended language. The results include a sound and complete proof theory for this extension. To ensure that the composite language constructs are adequately grounded in the pragmatic operation of robotic systems, Task Specification Trees (TSTs) and their mapping to these constructs are proposed. The expressive and pragmatic adequacy of this approach is demonstrated using an emergency response scenario.

2011
[110] Full text  Gianpaolo Conte and Patrick Doherty. 2011.
A Visual Navigation System for UAS Based on Geo-referenced Imagery.
In International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol. XXXVIII-1/C22Proceedings of the International Conference on Unmanned Aerial Vehicle in Geomatics, Zurich, Switzerland, September 14-16, 2011. In series: International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences #??.

[109] Full text  Patrick Doherty, Fredrik Heintz and David Landén. 2011.
A Delegation-Based Collaborative Robotic Framework.
In Christian Guttmann, editor, Proceedings of the 3rd International Workshop on Collaborative Agents - Research and development.
fulltext:postprint: http://liu.diva-portal.org/smash/get/div...

[108] Full text  Patrick Doherty and Fredrik Heintz. 2011.
A Delegation-Based Cooperative Robotic Framework.
In Proceedings of the IEEE International Conference on Robotics and Biomimetic, pages 2955–2962. IEEE conference proceedings. ISBN: 978-1-4577-2136-6.
DOI: 10.1109/ROBIO.2011.6181755.
fulltext:postprint: http://liu.diva-portal.org/smash/get/div...

Cooperative robotic systems, such as unmanned aircraft systems, are becoming technologically mature enough to be integrated into civil society. To gain practical use and acceptance, a verifiable, principled and well-defined foundation for interactions between human operators and autonomous systems is needed. In this paper, we propose and specify such a formally grounded collaboration framework. Collaboration is formalized in terms of the concept of delegation and delegation is instantiated as a speech act. Task Specification Trees are introduced as both a formal and pragmatic characterization of tasks and tasks are recursively delegated through a delegation process. The delegation speech act is formally grounded in the implementation using Task Specification Trees, task allocation via auctions and distributed constraint solving. The system is implemented as a prototype on unmanned aerial vehicle systems and a case study targeting emergency service applications is presented.

[107] Patrick Doherty, Barbara Dunin-Keplicz and Andrzej Szalas. 2011.
Tractable model checking for fragments of higher-order coalition logic.
In Liz Sonenberg, Peter Stone, Kagan Tumer, Pinar Yolum, editors, Proceedings of the 10th International Conference on Autonomous Agents and Multiagent Systems - Volume 2, pages 743–750. AAAI Press. ISBN: 0-9826571-6-1, 978-0-9826571-6-4.
Link: http://dl.acm.org/citation.cfm?id=203172...

A number of popular logical formalisms for representing and reasoning about the abilities of teams or coalitions of agents have been proposed beginning with the Coalition Logic (CL) of Pauly. Ågotnes et al introduced a means of succinctly expressing quantification over coalitions without compromising the computational complexity of model checking in CL by introducing Quantified Coalition Logic (QCL). QCL introduces a separate logical language for characterizing coalitions in the modal operators used in QCL. Boella et al, increased the representational expressibility of such formalisms by introducing Higher-Order Coalition Logic (HCL), a monadic second-order logic with special set grouping operators. Tractable fragments of HCL suitable for efficient model checking have yet to be identified. In this paper, we relax the monadic restriction used in HCL and restrict ourselves to the diamond operator. We show how formulas using the diamond operator are logically equivalent to second-order formulas. This permits us to isolate and define well-behaved expressive fragments of second-order logic amenable to model-checking in PTime. To do this, we appeal to techniques used in deductive databases and quantifier elimination. In addition, we take advantage of the monotonicity of the effectivity function resulting in exponentially more succinct representation of models. The net result is identification of highly expressible fragments of a generalized HCL where model checking can be done efficiently in PTime.

[106] Full text  Patrick Doherty, Tomasz Michalak, Jacek Sroka and Andrzej Szalas. 2011.
Contextual Coalitional Games.
In Mohua Banerjee, Anil Seth, editors, Proceedings of the 4th Indian Conference on Logic and its Applications (ICLA), pages 65–78. In series: Lecture Notes in Artificial Intelligence #6521. Springer Berlin/Heidelberg.
DOI: 10.1007/978-3-642-18026-2_7.

The study of cooperation among agents is of central interest in multi-agent systems research. A popular way to model cooperation is through coalitional game theory. Much research in this area has had limited practical applicability as regards real-world multi-agent systems due to the fact that it assumes<em>deterministic</em> payoffs to coalitions and in addition does not apply to multi-agent environments that are<em>stochastic</em> in nature. In this paper, we propose a novel approach to modeling such scenarios where coalitional games will be contextualized through the use of logical expressions representing environmental and other state, and probability distributions will be placed on the space of contexts in order to model the stochastic nature of the scenarios. More formally, we present a formal representation language for representing contextualized coalitional games embedded in stochastic environments and we define and show how to compute <em>expected Shapley values</em> in such games in a computationally efficient manner. We present the value of the approach through an example involving robotics assistance in emergencies.

2010
[105] Full text  Patrick Doherty, Jonas Kvarnström, Fredrik Heintz, David Landén and Per-Magnus Olsson. 2010.
Research with Collaborative Unmanned Aircraft Systems.
In Gerhard Lakemeyer, Hector J. Levesque, Fiora Pirri, editors, Proceedings of the Dagstuhl Workshop on Cognitive Robotics. In series: Dagstuhl Seminar Proceedings #10081. Leibniz-Zentrum für Informatik.

We provide an overview of ongoing research which targets development of a principled framework for mixed-initiative interaction with unmanned aircraft systems (UAS). UASs are now becoming technologically mature enough to be integrated into civil society. Principled interaction between UASs and human resources is an essential component in their future uses in complex emergency services or bluelight scenarios. In our current research, we have targeted a triad of fundamental, interdependent conceptual issues: delegation, mixed- initiative interaction and adjustable autonomy, that is being used as a basis for developing a principled and well-defined framework for interaction. This can be used to clarify, validate and verify different types of interaction between human operators and UAS systems both theoretically and practically in UAS experimentation with our deployed platforms.

[104] Full text  Piotr Rudol, Mariusz Wzorek and Patrick Doherty. 2010.
Vision-based Pose Estimation for Autonomous Indoor Navigation of Micro-scale Unmanned Aircraft Systems.
In Proceedings of the 2010 IEEE International Conference on Robotics and Automation (ICRA), pages 1913–1920. In series: Proceedings - IEEE International Conference on Robotics and Automation #2010. IEEE conference proceedings. ISBN: 978-1-4244-5038-1.
DOI: 10.1109/ROBOT.2010.5509203.

We present a navigation system for autonomous indoor flight of micro-scale Unmanned Aircraft Systems (UAS) which is based on a method for accurate monocular vision pose estimation. The method makes use of low cost artificial landmarks placed in the environment and allows for fully autonomous flight with all computation done on-board a UAS on COTS hardware. We provide a detailed description of all system components along with an accuracy evaluation and a time profiling result for the pose estimation method. Additionally, we show how the system is integrated with an existing micro-scale UAS and provide results of experimental autonomous flight tests. To our knowledge, this system is one of the first to allow for complete closed-loop control and goal-driven navigation of a micro-scale UAS in an indoor setting without requiring connection to any external entities.

[103] Full text  Mariusz Wzorek, Jonas Kvarnström and Patrick Doherty. 2010.
Choosing Path Replanning Strategies for Unmanned Aircraft Systems.
In Ronen Brafman, Héctor Geffner, Jörg Hoffmann, Henry Kautz, editors, Proceedings of the Twentieth International Conference on Automated Planning and Scheduling (ICAPS), pages 193–200. AAAI Press. ISBN: 978-1-57735-449-9.

Unmanned aircraft systems use a variety of techniques to plan collision-free flight paths given a map of obstacles and no- fly zones. However, maps are not perfect and obstacles may change over time or be detected during flight, which may in- validate paths that the aircraft is already following. Thus, dynamic in-flight replanning is required.Numerous strategies can be used for replanning, where the time requirements and the plan quality associated with each strategy depend on the environment around the original flight path. In this paper, we investigate the use of machine learn- ing techniques, in particular support vector machines, to choose the best possible replanning strategy depending on the amount of time available. The system has been implemented, integrated and tested in hardware-in-the-loop simulation with a Yamaha RMAX helicopter platform.

[102] Full text  Fredrik Heintz, Jonas Kvarnström and Patrick Doherty. 2010.
Stream-Based Reasoning in DyKnow.
In Gerhard Lakemeyer and Hector J. Levesque and Fiora Pirri, editors, Proceedings of the Dagstuhl Workshop on Cognitive Robotics. In series: Dagstuhl Seminar Proceedings #10081. Leibniz-Zentrum für Informatik.

The information available to modern autonomous systems is often in the form of streams. As the number of sensors and other stream sources increases there is a growing need for incremental reasoning about the incomplete content of sets of streams in order to draw relevant conclusions and react to new situations as quickly as possible. To act rationally, autonomous agents often depend on high level reasoning components that require crisp, symbolic knowledge about the environment. Extensive processing at many levels of abstraction is required to generate such knowledge from noisy, incomplete and quantitative sensor data. We define knowledge processing middleware as a systematic approach to integrating and organizing such processing, and argue that connecting processing components with streams provides essential support for steady and timely flows of information. DyKnow is a concrete and implemented instantiation of such middleware, providing support for stream reasoning at several levels. First, the formal kpl language allows the specification of streams connecting knowledge processes and the required properties of such streams. Second, chronicle recognition incrementally detects complex events from streams of more primitive events. Third, complex metric temporal formulas can be incrementally evaluated over streams of states. DyKnow and the stream reasoning techniques are described and motivated in the context of a UAV traffic monitoring application.

[101] Full text  Fredrik Heintz, Jonas Kvarnström and Patrick Doherty. 2010.
Stream-Based Middleware Support for Embedded Reasoning.
In Proceedings of the AAAI Spring Symposium on Embedded Reasoning: Intelligence in Embedded Systems (ER). AAAI Press. ISBN: 978-157735458-1.

For autonomous systems such as unmanned aerial vehicles to successfully perform complex missions, a great deal of embedded reasoning is required at varying levels of abstraction. In order to make use of diverse reasoning modules in such systems, issues of integration such as sensor data flow and information flow between such modules has to be taken into account. The DyKnow framework is a tool with a formal basis that pragmatically deals with many of the architectural issues which arise in such systems. This includes a systematic stream-based method for handling the sense-reasoning gap, caused by the wide difference in abstraction levels between the noisy data generally available from sensors and the symbolic, semantically meaningful information required by many high-level reasoning modules. DyKnow has proven to be quite robust and widely applicable to different aspects of hybrid software architectures for robotics.In this paper, we describe the DyKnow framework and show how it is integrated and used in unmanned aerial vehicle systems developed in our group. In particular, we focus on issues pertaining to the sense-reasoning gap and the symbol grounding problem and the use of DyKnow as a means of generating semantic structures representing situational awareness for such systems. We also discuss the use of DyKnow in the context of automated planning, in particular execution monitoring.

[100] Full text  Fredrik Heintz, Jonas Kvarnström and Patrick Doherty. 2010.
Stream-Based Reasoning Support for Autonomous Systems.
In Proceedings of the 19th European Conference on Artificial Intelligence (ECAI). In series: Frontiers in Artificial Intelligence and Applications #215. IOS Press. ISBN: 978-1-60750-605-8.
DOI: 10.3233/978-1-60750-606-5-183.

For autonomous systems such as unmanned aerial vehicles to successfully perform complex missions, a great deal of embedded reasoning is required at varying levels of abstraction. To support the integration and use of diverse reasoning modules we have developed DyKnow, a stream-based knowledge processing middleware framework. By using streams, DyKnow captures the incremental nature of sensor data and supports the continuous reasoning necessary to react to rapid changes in the environment. DyKnow has a formal basis and pragmatically deals with many of the architectural issues which arise in autonomous systems. This includes a systematic stream-based method for handling the sense-reasoning gap, caused by the wide difference in abstraction levels between the noisy data generally available from sensors and the symbolic, semantically meaningful information required by many highlevel reasoning modules. As concrete examples, stream-based support for anchoring and planning are presented.

[99] Full text  Fredrik Heintz and Patrick Doherty. 2010.
Federated DyKnow, a Distributed Information Fusion System for Collaborative UAVs.
In Proceedings of the 11th International Conference on Control, Automation, Robotics and Vision (ICARCV), pages 1063–1069. IEEE conference proceedings. ISBN: 978-1-4244-7814-9.
DOI: 10.1109/ICARCV.2010.5707967.

As unmanned aerial vehicle (UAV) applications are becoming more complex and covering larger physical areas there is an increasing need for multiple UAVs to cooperatively solve problems. To produce more complete and accurate information about the environment we present the DyKnow Federation framework for distributed fusion among collaborative UAVs. A federation is created and maintained using a multi-agent delegation framework which allows high-level specification and reasoning about resource bounded cooperative problem solving. When the federation is set up, local information is transparently shared between the agents according to specification. The work is presented in the context of a multi-UAV traffic monitoring scenario.

[98] Full text  Jonas Kvarnström and Patrick Doherty. 2010.
Automated Planning for Collaborative UAV Systems.
In Proceedings of the 11th International Conference on Control, Automation, Robotics and Vision (ICARCV), pages 1078–1085. IEEE conference proceedings. ISBN: 978-1-4244-7813-2, 978-1-4244-7814-9.
DOI: 10.1109/ICARCV.2010.5707969.
IEEE Explore: http://ieeexplore.ieee.org/xpls/abs_all....

Mission planning for collaborative Unmanned Aircraft Systems (UAS:s) is a complex topic which involves trade-offs between the degree of centralization or decentralization required, the degree of abstraction in which plans are generated, and the degree to which such plans are distributed among participating UAS:s. In realistic environments such as those found in naturaland man-made catastrophes where emergency services personnelare involved, a certain degree of centralization and abstractionis necessary in order for those in charge to understand andeventually sign off on potential plans. It is also quite often thecase that unconstrained distribution of actions is inconsistentwith the loosely coupled interactions and dependencies whicharise between collaborating systems. In this article, we presenta new planning algorithm for collaborative UAS:s based oncombining ideas from forward chaining planning with partialorderplanning leading to a new hybrid partial order forwardchaining(POFC) framework which meets the requirements oncentralization, abstraction and distribution we find in realisticemergency services settings.

[97] Full text  Per-Magnus Olsson, Jonas Kvarnström, Patrick Doherty, Oleg Burdakov and Kaj Holmberg. 2010.
Generating UAV Communication Networks for Monitoring and Surveillance.
In Proceedings of the 11th International Conference on Control, Automation, Robotics and Vision (ICARCV 2010), pages 1070–1077. IEEE conference proceedings. ISBN: 978-1-4244-7814-9.
DOI: 10.1109/ICARCV.2010.5707968.

An important use of unmanned aerial vehicles is surveillance of distant targets, where sensor information must quickly be transmitted back to a base station. In many cases, high uninterrupted bandwidth requires line-of-sight between sender and transmitter to minimize quality degradation. Communication range is typically limited, especially when smaller UAVs are used. Both problems can be solved by creating relay chains for surveillance of a single target, and relay trees for simultaneous surveillance of multiple targets. In this paper, we show how such chains and trees can be calculated. For relay chains we create a set of chains offering different trade-offs between the number of UAVs in the chain and the chain’s cost. We also show new results on how relay trees can be quickly calculated and then incrementally improved if necessary. Encouraging empirical results for improvement of relay trees are presented.

[96] Full text  Håkan Warnquist, Jonas Kvarnström and Patrick Doherty. 2010.
Iterative Bounding LAO*.
In Helder Coelho, Rudi Studer and Mike Wooldridge, editors, ECAI 2010: 19th European Conference on Artificial Intelligence - Volume 215 Frontiers in Artificial Intelligence and Applications, pages 341–346. In series: Frontiers in Artificial Intelligence and Applications #215. IOS Press. ISBN: 978-1-60750-605-8, 978-1-60750-606-5.
DOI: 10.3233/978-1-60750-606-5-341.

Iterative Bounding LAO* is a new algorithm for epsilon- optimal probabilistic planning problems where an absorbing goal state should be reached at a minimum expected cost from a given initial state. The algorithm is based on the LAO* algorithm for finding optimal solutions in cyclic AND/OR graphs. The new algorithm uses two heuristics, one upper bound and one lower bound of the optimal cost. The search is guided by the lower bound as in LAO*, while the upper bound is used to prune search branches. The algorithm has a new mechanism for expanding search nodes, and while maintaining the error bounds, it may use weighted heuristics to reduce the size of the explored search space. In empirical tests on benchmark problems, Iterative Bounding LAO* expands fewer search nodes compared to state of the art RTDP variants that also use two-sided bounds.

[95] Patrick Doherty and Andrzej Szalas. 2010.
On the Correctness of Rough-Set Based Approximate Reasoning.
In M. Szczuka, M. Kryszkiewicz, S. Ramanna, R. Jensen, Q. Hu, editors, Proceedings of the 7th International Conference on Rough Sets and Current Trends in Computing (RSCTC), pages 327–336. In series: Lecture Notes in Computer Science #6086. Springer. ISBN: 978-3-642-13528-6.
DOI: 10.1007/978-3-642-13529-3_35.

There is a natural generalization of an indiscernibility relation used in rough set theory, where rather than partitioning the universe of discourse into indiscernibility classes, one can consider a covering of the universe by similarity-based neighborhoods with lower and upper approximations of relations defined via the neighborhoods. When taking this step, there is a need to tune approximate reasoning to the desired accuracy. We provide a framework for analyzing self-adaptive knowledge structures. We focus on studying the interaction between inputs and output concepts in approximate reasoning. The problems we address are: -given similarity relations modeling approximate concepts, what are similarity relations for the output concepts that guarantee correctness of reasoning? -assuming that output similarity relations lead to concepts which are not accurate enough, how can one tune input similarities?

[94] Full text  Oleg Burdakov, Patrick Doherty, Kaj Holmberg, Jonas Kvarnström and Per-Magnus Olsson. 2010.
Positioning Unmanned Aerial Vehicles As Communication Relays for Surveillance Tasks.
In J. Trinkle, Y. Matsuoka and J.A. Castellanos, editors, Robotics: Science and Systems V, pages 257–264. MIT Press. ISBN: 978-0-262-51463-7.
find book at a swedish library/hitta boken i ett svenskt bibliotek: http://libris.kb.se/bib/12536749
Link to publication: http://www.roboticsproceedings.org/rss05...

When unmanned aerial vehicles (UAVs) are used to survey distant targets, it is important to transmit sensor information back to a base station. As this communication often requires high uninterrupted bandwidth, the surveying UAV often needs afree line-of-sight to the base station, which can be problematic in urban or mountainous areas. Communication ranges may also belimited, especially for smaller UAVs. Though both problems can be solved through the use of relay chains consisting of one or more intermediate relay UAVs, this leads to a new problem: Where should relays be placed for optimum performance? We present two new algorithms capable of generating such relay chains, one being a dual ascent algorithm and the other a modification of the Bellman-Ford algorithm. As the priorities between the numberof hops in the relay chain and the cost of the chain may vary, wecalculate chains of different lengths and costs and let the ground operator choose between them. Several different formulations for edge costs are presented. In our test cases, both algorithms are substantially faster than an optimized version of the original Bellman-Ford algorithm, which is used for comparison.

2009
[93] Full text  Håkan Warnquist, Jonas Kvarnström and Patrick Doherty. 2009.
Planning as Heuristic Search for Incremental Fault Diagnosis and Repair.
In Proceedings of the Scheduling and Planning Applications Workshop (SPARK) at the 19th International Conference on Automated Planning and Scheduling (ICAPS).

In this paper we study the problem of incremental fault diagnosis and repair of mechatronic systems where the task is to choose actions such that the expected cost of repair is minimal. This is done by interleaving acting with the generation of partial conditional plans used to decide the next action. A diagnostic model based on Bayesian Networks is used to update the current belief state after each action. The planner uses a simplified version of this model to update predicted belief states. We have tested the approach in the domain of troubleshooting heavy vehicles. Experiments show that a simplified model for planning improves performance when troubleshooting with limited time.

[92] Full text  Martin Magnusson, David Landén and Patrick Doherty. 2009.
Logical Agents that Plan, Execute, and Monitor Communication.
In Proceedings of the 2nd Workshop on Logic and the Simulation of Interaction and Reasoning (LSIR-2).

[91] Full text  Martin Magnusson and Patrick Doherty. 2009.
Planning Speech Acts in a Logic of Action and Change.
In Fredrik Heintz and Jonas Kvarnström, editors, The Swedish AI Society Workshop 2009, SAIS 2009, pages 39–48. In series: Linköping Electronic Conference Proceedings #35. Linköping University Electronic Press, Linköpings universitet.
Fulltext: http://www.ep.liu.se/ecp/035/008/ecp0935...

Cooperation is a complex task that necessarily involves communication and reasoning about others’ intentions and beliefs. Multi-agent communication languages aid designers of cooperating robots through standardized speech acts, sometimes including a formal semantics. But a more direct approach would be to have the robots plan both regular and communicative actions themselves. We show how two robots with heterogeneous capabilities can autonomously decide to cooperate when faced with a task that would otherwise be impossible. Request and inform speech acts are formulated in the same first-order logic of action and change as is used for regular actions. This is made possible by treating the contents of communicative actions as quoted formulas of the same language. The robot agents then use a natural deduction theorem prover to generate cooperative plans for an example scenario by reasoning directly with the axioms of the theory.

[90] Full text  Fredrik Heintz, Jonas Kvarnström and Patrick Doherty. 2009.
Stream Reasoning in DyKnow: A Knowledge Processing Middleware System.
In Proceedings of the Stream Reasoning Workshop. In series: CEUR Workshop Proceedings #466. M. Jeusfeld c/o Redaktion Sun SITE, Informatik V, RWTH Aachen.

The information available to modern autonomous systems is often in the form of streams. As the number of sensors and other stream sources increases there is a growing need for incremental reasoning about the incomplete content of sets of streams in order to draw relevant conclusions and react to new situations as quickly as possible. To act rationally, autonomous agents often depend on high level reasoning components that require crisp, symbolic knowledge about the environment. Extensive processing at many levels of abstraction is required to generate such knowledge from noisy, incomplete and quantitative sensor data. We define knowledge processing middleware as a systematic approach to integrating and organizing such processing, and argue that connecting processing components with streams provides essential support for steady and timely flows of information. DyKnow is a concrete and implemented instantiation of such middleware, providing support for stream reasoning at several levels. First, the formal KPL language allows the specification of streams connecting knowledge processes and the required properties of such streams. Second, chronicle recognition incrementally detects complex events from streams of more primitive events. Third, complex metric temporal formulas can be incrementally evaluated over streams of states. DyKnow and the stream reasoning techniques are described and motivated in the context of a UAV traffic monitoring application.

[89] Full text  Martin Magnusson, Jonas Kvarnström and Patrick Doherty. 2009.
Abductive Reasoning with Filtered Circumscription.
In Proceedings of the IJCAI-09 Workshop on Nonmonotonic Reasoning, Action and Change (NRAC). UTSePress. ISBN: 978-0-9802840-7-2.

For logical artificial intelligence to be truly useful,its methods must scale to problems of realistic size.An interruptible algorithm enables a logical agentto act in a timely manner to the best of its knowledge,given its reasoning so far. This seems necessaryto avoid analysis paralysis, trying to thinkof every potentiality, however unlikely, beforehand.These considerations prompt us to look for alternativereasoning mechanisms for filtered circumscription,a nonmonotonic reasoning formalism usede.g. by Temporal Action Logic and Event Calculus.We generalize Ginsberg’s circumscriptive theoremprover and describe an interruptible theoremprover based on abduction that has been used tounify planning and reasoning in a logical agent architecture.

[88] Full text  Fredrik Heintz, Jonas Kvarnström and Patrick Doherty. 2009.
A Stream-Based Hierarchical Anchoring Framework.
In Proceedings of the IEEE/RSJ International Conference on Intelligent RObots and Systems (IROS). IEEE conference proceedings. ISBN: 978-1-4244-3803-7.
DOI: 10.1109/IROS.2009.5354372.
IEEE Xplore: http://ieeexplore.ieee.org/stamp/stamp.j...

2008
[87] Gianpaolo Conte and Patrick Doherty. 2008.
Use of Geo-referenced Images with Unmanned Aerial Systems.
In Workshop Proceedings of SIMPAR 2008, International Conference on Simulation, Modeling and Programming for Autonomous Robots. Venice(Italy) 2008 November,3-4., pages 444–454. ISBN: 978-88-95872-01-8.

[86] Full text  Per Nyblom and Patrick Doherty. 2008.
Towards Automatic Model Generation by Optimization.
In Proceedings of the Tenth Scandinavian Conference on Artificial Intelligence (SCAI), pages 114–123. In series: Frontiers in Artificial Intelligence and Applications #173. IOS Press. ISBN: 978-1-58603-867-0, e-978-1-60750-335-4.
Link to publication: http://www.booksonline.iospress.nl/Conte...

The problem of automatically selecting simulation models for autonomous agents depending on their current intentions and beliefs is considered in this paper. The intended use of the models is for prediction, filtering, planning and other types of reasoning that can be performed with Simulation models. The parameters and model fragments of the resulting model are selected by formulating and solving a hybrid constrained optimization problem that captures the intuition of the preferred model when relevance information about the elements of the world being modelled is taken into consideration. A specialized version of the original optimization problem is developed that makes it possible to solve the continuous subproblem analytically in linear time. A practical model selection problem is discussed where the aim is to select suitable parameters and models for tracking dynamic objects. Experiments with randomly generated problem instances indicate that a hillclimbing search approach might be both efficient and provides reasonably good solutions compared to simulated annealing and hillclimbing with random restarts.

[85] Full text  Gianpaolo Conte and Patrick Doherty. 2008.
An Integrated UAV Navigation System Based on Aerial Image Matching.
In IEEE Aerospace Conference 2008,2008, pages 3142–3151. In series: IEEE Aerospace Conference #??. IEEE. ISBN: 978-1-4244-1487-1, 978-1-4244-1488-8.
DOI: 10.1109/AERO.2008.4526556.

The aim of this paper is to explore the possibility of using geo-referenced satellite or aerial images to augment an Unmanned Aerial Vehicle (UAV) navigation system in case of GPS failure. A vision based navigation system which combines inertial sensors, visual odometer and registration of a UAV on-board video to a given geo-referenced aerial image has been developed and tested on real flight-test data. The experimental results show that it is possible to extract useful position information from aerial imagery even when the UAV is flying at low altitude. It is shown that such information can be used in an automated way to compensate the drift of the UAV state estimation which occurs when only inertial sensors and visual odometer are used.

[84] Full text  Gianpaolo Conte, Maria Hempel, Piotr Rudol, David Lundström, Simone Duranti, Mariusz Wzorek and Patrick Doherty. 2008.
High Accuracy Ground Target Geo-Location Using Autonomous Micro Aerial Vehicle Platforms.
In Proceedings of the AIAA Guidance, Navigation, and Control Conference (GNC). AIAA. ISBN: 978-1-56347-945-8.

This paper presents a method for high accuracy ground target localization using a Micro Aerial Vehicle (MAV) equipped with a video camera sensor. The proposed method is based on a satellite or aerial image registration technique. The target geo-location is calculated by registering the ground target image taken from an on-board video camera with a geo- referenced satellite image. This method does not require accurate knowledge of the aircraft position and attitude, therefore it is especially suitable for MAV platforms which do not have the capability to carry accurate sensors due to their limited payload weight and power resources. The paper presents results of a ground target geo-location experiment based on an image registration technique. The platform used is a MAV prototype which won the 3rd US-European Micro Aerial Vehicle Competition (MAV07). In the experiment a ground object was localized with an accuracy of 2.3 meters from a ight altitude of 70 meters.

[83] Full text  Piotr Rudol and Patrick Doherty. 2008.
Human Body Detection and Geolocalization for UAV Search and Rescue Missions Using Color and Thermal Imagery.
In Proceedings of the IEEE Aerospace Conference, pages 1–8. In series: Aerospace Conference Proceedings #2008. IEEE. ISBN: 978-1-4244-1488-8, 978-1-4244-1487-1.
DOI: 10.1109/AERO.2008.4526559.

Recent advances in the field of Unmanned Aerial Vehicles (UAVs) make flying robots suitable platforms for carrying sensors and computer systems capable of performing advanced tasks. This paper presents a technique which allows detecting humans at a high frame rate on standard hardware onboard an autonomous UAV in a real-world outdoor environment using thermal and color imagery. Detected human positions are geolocated and a map of points of interest is built. Such a saliency map can, for example, be used to plan medical supply delivery during a disaster relief effort. The technique has been implemented and tested on-board the UAVTech<sup>1</sup> autonomous unmanned helicopter platform as a part of a complete autonomous mission. The results of flight- tests are presented and performance and limitations of the technique are discussed.

[82] Patrick Doherty and Andrzej Szalas. 2008.
Reasoning with Qualitative Preferences and Cardinalities Using Generalized Circumscription.
In Gerhard Brewka, Jérôme Lang, editors, Proceedings of the 11th International Conference on Principles of Knowledge Representation and Reasoning (KR), pages 560–570. AAAI Press. ISBN: 978-1-57735-384-3.

The topic of preference modeling has recently attracted the interest of a number of sub-disciplines in artificial intelligence such as the nonmonotonic reasoning and action and change communities. The approach in these communities focuses on qualitative preferences and preference models which provide more natural representations from a~commonsense perspective. In this paper, we show how generalized circumscription can be used as a highly expressive framework for qualitative preference modeling. Generalized circumscription proposed by Lifschitz allows for predicates (and thus formulas) to be minimized relative to arbitrary pre-orders (reflexive and transitive). Although it has received little attention, we show how it may be used to model and reason about elaborate qualitative preference relations. One of the perceived weaknesses with any type of circumscription is the 2nd-order nature of the representation. The paper shows how a large variety of preference theories represented using generalized circumscription can in fact be reduced to logically equivalent first-order theories in a constructive way. Finally, we also show how preference relations represented using general circumscription can be extended with cardinality constraints and when these extensions can also be reduced to logically equivalent first-order theories.

[81] Full text  Fredrik Heintz and Patrick Doherty. 2008.
DyKnow Federations: Distributing and Merging Information Among UAVs.
In Proceedings of the 11th International Conference on Information Fusion (FUSION). IEEE conference proceedings. ISBN: 978-3-8007-3092-6.

As unmanned aerial vehicle (UAV) applications become more complex and versatile there is an increasing need to allow multiple UAVs to cooperate to solve problems which are beyond the capability of each individual UAV. To provide more complete and accurate information about the environment we present a DyKnow federation framework for information integration in multi-node networks of UAVs. A federation is created and maintained using a multiagent delegation framework and allows UAVs to share local information as well as process information from other UAVs as if it were local using the DyKnow knowledge processing middleware framework. The work is presented in the context of a multi UAV traffic monitoring scenario.

[80] Full text  Martin Magnusson and Patrick Doherty. 2008.
Temporal Action Logic for Question Answering in an Adventure Game.
In Artificial General Intelligence, AGI 2008, pages 236–247. In series: Frontiers in Artificial Intelligence and Applications #15. IOS Press. ISBN: 978-1-58603-833-5.

Inhabiting the complex and dynamic environments of modern computer games with autonomous agents capable of intelligent timely behaviour is a significant research challenge. We illustrate this using Our own attempts to build a practical agent architecture on it logicist foundation. In the ANDI-Land adventure game concept players solve puzzles by eliciting information from computer characters through natural language question answering. While numerous challenges immediately presented themselves, they took on a form of concrete and accessible problems to solve, and we present some of our initial solutions. We conclude that games, due to their demand for human-like computer characters with robust and independent operation in large simulated worlds, might serve as excellent test beds for research towards artificial general intelligence.

[79] Full text  Martin Magnusson, David Landén and Patrick Doherty. 2008.
Planning, Executing, and Monitoring Communication in a Logic-Based Multi-Agent System.
In ECAI 2008, pages 933–934. In series: Frontiers in Artificial Intelligence and Applications #178. IOS Press. ISBN: 978-1-58603-891-5.
DOI: 10.3233/978-1-58603-891-5-933.

[78] Full text  Martin Magnusson and Patrick Doherty. 2008.
Deductive Planning with Inductive Loops.
In Proceedings of the 11th International Conference on Principles of Knowledge Representation and Reasoning (KR), pages 528–534. AAAI Press. ISBN: 978-1-57735-384-3.

Agents plan to achieve and maintain goals. Maintenance that requires continuous action excludes the representation of plans as finite sequences of actions. If there is no upper bound on the number of actions, a simple list of actions would be infinitely long. Instead, a compact representation requires some form of looping construct. We look at a specific temporally extended maintenance goal, multiple target video surveillance, and formalize it in Temporal Action Logic. The logic's representation of time as the natural numbers suggests using mathematical induction to deductively plan to satisfy temporally extended goals. Such planning makes use of a sound and useful, but incomplete, induction rule that compactly represents the solution as a recursive fixpoint formula. Two heuristic rules overcome the problem of identifying a sufficiently strong induction hypothesis and enable an automated solution to the surveillance problem that satisfies the goal indefinitely.

[77] Full text  Martin Magnusson and Patrick Doherty. 2008.
Logical Agents for Language and Action.
In 4th International Artificial Intelligence and Interactive Digital Entertainment Conference AIIDE 2008,2008. AAAI Press. ISBN: 978-1-57735-391-1.

[76] Full text  Fredrik Heintz, Jonas Kvarnström and Patrick Doherty. 2008.
Bridging the Sense-Reasoning Gap: DyKnow - A Middleware Component for Knowledge Processing.
In Martin Hulse and Manfred Hild, editors, IROS Workshop on Current Software Frameworks in Cognitive Robotics Integrating Different Computational Paradigms.
Note: No proceedings, but CD

Developing autonomous agents displaying rational and goal-directed behavior in a dynamic physical environment requires the integration of both sensing and reasoning components. Due to the different characteristics of these components there is a gap between sensing and reasoning. We believe that this gap can not be bridged in a single step with a single technique. Instead, it requires a more general approach to integrating components on many different levels of abstraction and organizing them in a structured and principled manner. In this paper we propose knowledge processing middleware as a systematic approach for organizing such processing. Desirable properties of such middleware are presented and motivated. We then go on to argue that a declarative streambased system is appropriate to provide the desired functionality. Finally, DyKnow, a concrete example of stream-based knowledge processing middleware that can be used to bridge the sense-reasoning gap, is presented. Different types of knowledge processes and components of the middleware are described and motivated in the context of a UAV traffic monitoring application.

[75] Full text  Jonas Kvarnström, Fredrik Heintz and Patrick Doherty. 2008.
A Temporal Logic-Based Planning and Execution Monitoring System.
In Proceedings of the International Conference on Automated Planning and Scheduling (ICAPS). AAAI Press. ISBN: 978-1-57735-386-7, 978-1-57735-387-4.

As no plan can cover all possible contingencies, the ability to detect failures during plan execution is crucial to the robustness of any autonomous system operating in a dynamic and uncertain environment. In this paper we present a general planning and execution monitoring system where formulas in an expressive temporal logic specify the desired behavior of a system and its environment. A unified domain description for planning and monitoring provides a solid shared declarative semantics permitting the monitoring of both global and operator-specific conditions. During plan execution, an execution monitor subsystem detects violations of monitor formulas in a timely manner using a progression algorithm on incrementally generated partial logical models. The system has been integrated on a fully deployed autonomous unmanned aircraft system. Extensive empirical testing has been performed using a combination of actual flight tests and hardware-in-the-loop simulations in a number of different mission scenarios.

[74] Full text  Per-Magnus Olsson and Patrick Doherty. 2008.
The Observer Algorithm For Visibility Approximation.
In 10th Scandinavian Conference on Artificial Intelligence, SCAI 2008, pages 3–11. In series: Frontiers in Artificial Intelligence and Applications #173. IOS Press. ISBN: 978-1-58603-867-0, e-978-1-60750-335-4.
Link to paper: http://books.google.se/books?id=eju691VM...

We present a novel algorithm for visibility approximation that is substantially faster than ray casting based algorithms. The algorithm does not require extensive preprocessing or specialized hardware as most other algorithms do. We test this algorithm in several settings: rural, mountainous and urban areas, with different view ranges and grid cell sizes. By changing the size of the grid cells that the algorithm uses, it is possible to tailor the algorithm between speed and accuracy.

[73] Full text  Piotr Rudol, Mariusz Wzorek, Gianpaolo Conte and Patrick Doherty. 2008.
Micro unmanned aerial vehicle visual servoing for cooperative indoor exploration.
In Proceedings of the IEEE Aerospace Conference. In series: Aerospace Conference Proceedings #2008. IEEE conference proceedings. ISBN: 978-1-4244-1487-1.
DOI: 10.1109/AERO.2008.4526558.

Recent advances in the field of micro unmanned aerial vehicles (MAVs) make flying robots of small dimensions suitable platforms for performing advanced indoor missions. In order to achieve autonomous indoor flight a pose estimation technique is necessary. This paper presents a complete system which incorporates a vision-based pose estimation method to allow a MAV to navigate in indoor environments in cooperation with a ground robot. The pose estimation technique uses a lightweight light emitting diode (LED) cube structure as a pattern attached to a MAV. The pattern is observed by a ground robot's camera which provides the flying robot with the estimate of its pose. The system is not confined to a single location and allows for cooperative exploration of unknown environments. It is suitable for performing missions of a search and rescue nature where a MAV extends the range of sensors of the ground robot. The performance of the pose estimation technique and the complete system is presented and experimental flights of a vertical take-off and landing (VTOL) MAV are described.

[72] Full text  Fredrik Heintz, Jonas Kvarnström and Patrick Doherty. 2008.
Knowledge Processing Middleware.
In S. Carpin, I. Noda, E. Pagello, M. Reggiani and O. von Stryk, editors, Proceedings of the 1st International Conference on Simulation, Modeling, and Programming for Autonomous Robots (SIMPAR), pages 147–158. In series: Lecture Notes in Computer Science #5325. Springer. ISBN: 978-3-540-89075-1, 978-3-540-89076-8.
DOI: 10.1007/978-3-540-89076-8_17.
fulltext:preprint: http://liu.diva-portal.org/smash/get/div...

Developing autonomous agents displaying rational and goal-directed behavior in a dynamic physical environment requires the integration of a great number of separate deliberative and reactive functionalities. This integration must be built on top of a solid foundation of data, information and knowledge having numerous origins, including quantitative sensors and qualitative knowledge databases. Processing is generally required on many levels of abstraction and includes refinement and fusion of noisy sensor data and symbolic reasoning. We propose the use of knowledge processing middleware as a systematic approach for organizing such processing. Desirable properties of such middleware are presented and motivated. We then argue that a declarative stream-based system is appropriate to provide the desired functionality. Different types of knowledge processes and components of the middleware are described and motivated in the context of a UAV traffic monitoring application. Finally DyKnow, a concrete example of stream-based knowledge processing middleware, is briefly described.

2007
[71] Full text  Simone Duranti, Gianpaolo Conte, David Lundström, Piotr Rudol, Mariusz Wzorek and Patrick Doherty. 2007.
LinkMAV, a prototype rotary wing micro aerial vehicle.
In 17th IFAC Symposium on Automatic Control in Aerospace,2007. Elsevier.

[70] Patrick Doherty, Barbara Dunin-Keplicz and Andrzej Szalas. 2007.
Dynamics of approximate information fusion.
In Proceedings of the International Conference on Rough Sets and Emerging Intelligent Systems Paradigms (RSEISP), pages 668–677. In series: Lecture Notes in Artificial Intelligence #4585. Springer Berlin/Heidelberg. ISBN: 978-3-540-73450-5.
DOI: 10.1007/978-3-540-73451-2_70.

The multi-agent system paradigm has proven to be a useful means of abstraction when considering distributed systems with interacting components. It is often the case that each component may be viewed as an intelligent agent with specific and often limited perceptual capabilities. It is also the case that these agent components may be used as information sources and such sources may be aggregated to provide global information about particular states, situations or activities in the embedding environment. This paper investigates a framework for information fusion based on the use of generalizations of rough set theory and the use of dynamic logic as a basis for aggregating similarity relations among objects where the similarity relations represent individual agents perceptual capabilities or limitations. As an added benefit, it is shown how this idea may also be integrated into description logics.

[69] Patrick Doherty and John-Jules Meyer. 2007.
Towards a delegation framework for aerial robotic mission scenarios.
In Proceedings of the 11th International Workshop on Cooperative Information Agents (CIA), pages 5–26. Springer Berlin/Heidelberg. ISBN: 978-3-540-75118-2.
DOI: 10.1007/978-3-540-75119-9_2.

The concept of delegation is central to an understanding of the interactions between agents in cooperative agent problem-solving contexts. In fact, the concept of delegation offers a means for studying the formal connections between mixed-initiative problem-solving, adjustable autonomy and cooperative agent goal achievement. In this paper, we present an exploratory study of the delegation concept grounded in the context of a relatively complex multi-platform Unmanned Aerial Vehicle (UAV) catastrophe assistance scenario, where UAVs must cooperatively scan a geographic region for injured persons. We first present the scenario as a case study, showing how it is instantiated with actual UAV platforms and what a real mission implies in terms of pragmatics. We then take a step back and present a formal theory of delegation based on the use of 2APL and KARO. We then return to the scenario and use the new theory of delegation to formally specify many of the communicative interactions related to delegation used in achieving the goal of cooperative UAV scanning. The development of theory and its empirical evaluation is integrated from the start in order to ensure that the gap between this evolving theory of delegation and its actual use remains closely synchronized as the research progresses. The results presented here may be considered a first iteration of the theory and ideas.

[68] Full text  Patrick Doherty and Piotr Rudol. 2007.
A UAV search and rescue scenario with human body detection and geolocalization.
In Proceedings of the 20th Australian Joint Conference on Artificial Intelligence (AI). Springer Berlin/Heidelberg. ISBN: 978-3-540-76926-2.

The use of Unmanned Aerial Vehicles (UAVs) which can operate autonomously in dynamic and complex operational environments is becoming increasingly more common. The UAVTech Lab, is pursuing a long term research endeavour related to the development of future aviation systems which try and push the envelope in terms of using and integrating high-level deliberative or AI functionality with traditional reactive and control components in autonomous UAV systems. In order to carry on such research, one requires challenging mission scenarios which force such integration and development. In this paper, one of these challenging emergency services mission scenarios is presented. It involves search and rescue for injured civilians by UAVs. In leg I of the mission, UAVs scan designated areas and try to identify injured civilians. In leg II of the mission, an attempt is made to deliver medical and other supplies to identified victims. We show how far we have come in implementing and executing such a challenging mission in realistic urban scenarios.

[67] Full text  Luis Mejias, Pascual Campoy, Iván F. Mondragón and Patrick Doherty. 2007.
Stereo visual system for autonomous air vehicle navigation.
In 6th IFAC Symposium on Intelligent Autonomous Vehicles (2007) Intelligent Autonomous Vehicles, Volume# 6 | Part# 1, pages 203–208. In series: IFAC Proceedings series #??. Elsevier. ISBN: 978-3-902661-65-4.
DOI: 10.3182/20070903-3-FR-2921.00037.

We present a system to estimate the altitude and motion of an aerial vehicle using a stereo visual system. The system has been initially tested on a ground robot and the novelty lays on its application and robustness validation in an UAV, where vibrations and rapid environmental changes take place. The two main functionalities are height estimation and visual odometry. The system first detects and tracks salient points in the scene. Depth to the plane containing the features is calculated matching features between left and right images then using the disparity principle. Motion is recovered tracking pixels from one frame to the next one finding its visual displacement and resolving camera rotation and translation by a least-square method. We present results from different experimental trials on the two platforms comparing and discussing the results regarding the trajectories calculated by the visual odometry and the onboard helicopter state estimation.

[66] Full text  Fredrik Heintz, Piotr Rudol and Patrick Doherty. 2007.
From Images to Traffic Behavior - A UAV Tracking and Monitoring Application.
In Proceedings of the 10th International Conference on Information Fusion (FUSION). IEEE conference proceedings. ISBN: 978-0-662-45804-3, 978-0-662-47830-0.
DOI: 10.1109/ICIF.2007.4408103.
Link: http://www.ida.liu.se/~frehe/publication...

An implemented system for achieving high level situation awareness about traffic situations in an urban area is described. It takes as input sequences of color and thermal images which are used to construct and maintain qualitative object structures and to recognize the traffic behavior of the tracked vehicles in real time. The system is tested both in simulation and on data collected during test flights. To facilitate the signal to symbol transformation and the easy integration of the streams of data from the sensors with the GIS and the chronicle recognition system, DyKnow, a stream-based knowledge processing middleware, is used. It handles the processing of streams, including the temporal aspects of merging and synchronizing streams, and provides suitable abstractions to allow high level reasoning and narrow the sense reasoning gap.

[65] Full text  Fredrik Heintz, Piotr Rudol and Patrick Doherty. 2007.
Bridging the Sense-Reasoning Gap Using DyKnow: A Knowledge Processing Middleware Framework.
In Joachim Hertzberg, Michael Beetz and Roman Englert, editors, Proceedings of the 30th Annual German Conference on Artificial Intelligence (KI), pages 460–463. In series: Lecture Notes in Computer Science #4667. Springer. ISBN: 978-3-540-74564-8.
DOI: 10.1007/978-3-540-74565-5_40.
Link: http://www.ida.liu.se/~frehe/publication...

To achieve complex missions an autonomous unmanned aerial vehicle (UAV) operating in dynamic environments must have and maintain situational awareness. This can be achieved by continually gathering information from many sources, selecting the relevant information for current tasks, and deriving models about the environment and the UAV itself. It is often the case models suitable for traditional control, are not sufficient for deliberation. The need for more abstract models creates a sense-reasoning gap. This paper presents DyKnow, a knowledge processing middleware framework, and shows how it supports bridging the gap in a concrete UAV traffic monitoring application. In the example, sequences of color and thermal images are used to construct and maintain qualitative object structures. They model the parts of the environment necessary to recognize traffic behavior of tracked vehicles in real-time. The system has been implemented and tested in simulation and on data collected during flight tests.

[64] Full text  Martin Magnusson and Patrick Doherty. 2007.
Deductive Planning with Temporal Constraints.
In Commonsense 2007, the 8th International Symposium on Logical Formalizations of Commonsense Reasoning,2007. AAAI Press. ISBN: 978-1-57735-314-0.
Link: http://www.ucl.ac.uk/commonsense07/paper...

Temporal Action Logic is a well established logical formalism for reasoning about action and change using an explicit time representation that makes it suitable for applications that involve complex temporal reasoning. We take advantage of constraint satisfaction technology to facilitate such reasoning through temporal constraint networks. Extensions are introduced that make generation of action sequences possible, thus paving the road for interesting applications in deductive planning. The extended formalism is encoded as a logic program that is able to realize a least commitment strategy that generates partial order plans in the context of both qualitative and quantitative temporal constraints.

2006
[63] Full text  Alexander Kleiner, Christian Dornhege, Rainer Kümmerle, Michael Ruhnke, Bastian Steder, Bernhard Nebel, Patrick Doherty, Mariusz Wzorek, Piotr Rudol, Gianpaolo Conte, Simone Duranti and David Lundström. 2006.
RoboCupRescue - Robot League Team RescueRobots Freiburg (Germany).
In RoboCup 2006 (CDROM Proceedings), Team Description Paper, Rescue Robot League.
Note: (1st place in the autonomy competition)
fulltext:postprint: http://liu.diva-portal.org/smash/get/div...

This paper describes the approach of the RescueRobots Freiburg team, which is a team of students from the University of Freiburg that originates from the former CS Freiburg team (RoboCupSoccer) and the ResQ Freiburg team (RoboCupRescue Simulation). Furthermore we introduce linkMAV, a micro aerial vehicle platform. Our approach covers RFID-based SLAM and exploration, autonomous detection of relevant 3D structures, visual odometry, and autonomous victim identification. Furthermore, we introduce a custom made 3D Laser Range Finder (LRF) and a novel mechanism for the active distribution of RFID tags.

[62] Full text  Martin Magnusson and Patrick Doherty. 2006.
Deductive Planning with Temporal Constraints using TAL.
In Proceedings of the International Symposium on Practical Cognitive Agents and Robots (PCAR). UWA Press. ISBN: 1-74052-130-7.
DOI: 10.1145/1232425.1232444.

Temporal Action Logic is a well established logical formalism for reasoning about action and change using an explicit time representation that makes it suitable for applications that involve complex temporal reasoning. We take advantage of constraint satisfaction technology to facilitate such reasoning through temporal constraint networks. Extensions are introduced that make generation of action sequences possible, thus paving the road for interesting applications in deductive planning. The extended formalism is encoded as a logic program that is able to realize a least commitment strategy that generates partial order plans in the context of both qualitative and quantitative temporal constraints.

[61] Full text  Mariusz Wzorek, David Landén and Patrick Doherty. 2006.
GSM Technology as a Communication Media for an Autonomous Unmanned Aerial Vehicle.
In Proceedings of the 21st Bristol International UAV Systems Conference (UAVS). University of Bristol, Department of Aerospace engineering. ISBN: 0-9552644-0-5.
Note: ISBN: 0-9552644-0-5

[60] Full text  Mariusz Wzorek, Gianpaolo Conte, Piotr Rudol, Torsten Merz, Simone Duranti and Patrick Doherty. 2006.
From Motion Planning to Control - A Navigation Framework for an Autonomous Unmanned Aerial Vehicle.
In Proceedings of the 21st Bristol UAV Systems Conference (UAVS).
Link to Ph.D. Thesis: http://urn.kb.se/resolve?urn=urn:nbn:se:...

The use of Unmanned Aerial Vehicles (UAVs) which can operate autonomously in dynamic and complex operational environments is becoming increasingly more common. While the application domains in which they are currently used are still predominantly military in nature, in the future we can expect wide spread usage in thecivil and commercial sectors. In order to insert such vehicles into commercial airspace, it is inherently important that these vehicles can generate collision-free motion plans and also be able to modify such plans during theirexecution in order to deal with contingencies which arise during the course of operation. In this paper, wepresent a fully deployed autonomous unmanned aerial vehicle, based on a Yamaha RMAX helicopter, whichis capable of navigation in urban environments. We describe a motion planning framework which integrates two sample-based motion planning techniques, Probabilistic Roadmaps and Rapidly Exploring Random Treestogether with a path following controller that is used during path execution. Integrating deliberative services, suchas planners, seamlessly with control components in autonomous architectures is currently one of the major open problems in robotics research. We show how the integration between the motion planning framework and thecontrol kernel is done in our system.Additionally, we incorporate a dynamic path reconfigurability scheme. It offers a surprisingly efficient method for dynamic replanning of a motion plan based on unforeseen contingencies which may arise during the execution of a plan. Those contingencies can be inserted via ground operator/UAV interaction to dynamically change UAV flight paths on the fly. The system has been verified through simulation and in actual flight. We present empirical results of the performance of the framework and the path following controller.

[59] Full text  Mariusz Wzorek and Patrick Doherty. 2006.
The WITAS UAV Ground System Interface Demonstration with a Focus on Motion and Task Planning.
In Software Demonstrations at the International Conference on Automated Planning Scheduling (ICAPS-SD), pages 36–37.

The Autonomous UAV Technologies Laboratory at Linköping University, Sweden, has been developing fully autonomous rotor-based UAV systems in the mini- and micro-UAV class. Our current system design is the result of an evolutionary process based on many years of developing, testing and maintaining sophisticated UAV systems. In particular, we have used the Yamaha RMAX helicopter platform(Fig. 1) and developed a number of micro air vehicles from scratch.

[58] Full text  Mariusz Wzorek and Patrick Doherty. 2006.
Reconfigurable Path Planning for an Autonomous Unmanned Aerial Vehicle.
In Derek Long, Stephen F. Smith, Daniel Borrajo, Lee McCluskey, editors, Proceedings of the Sixteenth International Conference on Automated Planning and Scheduling (ICAPS), pages 438–441. AAAI Press. ISBN: 978-1-57735-270-9.

In this paper, we present a motion planning framework for a fully deployed autonomous unmanned aerial vehicle which integrates two sample-based motion planning techniques, Probabilistic Roadmaps and Rapidly Exploring Random Trees. Additionally, we incorporate dynamic reconfigurability into the framework by integrating the motion planners with the control kernel of the UAV in a novel manner with little modification to the original algorithms. The framework has been verified through simulation and in actual flight. Empirical results show that these techniques used with such a framework offer a surprisingly efficient method for dynamically reconfiguring a motion plan based on unforeseen contingencies which may arise during the execution of a plan. The framework is generic and can be used for additional platforms.

[57] Full text  Mariusz Wzorek and Patrick Doherty. 2006.
Reconfigurable Path Planning for an Autonomous Unmanned Aerial Vehicle.
In ICHIT 2006 - International Conference on Hybrid Information Technology,2006.

2005
[56] Full text  Patrick Doherty, Andrzej Szalas and Witold Lukaszewicz. 2005.
Similarity, approximations and vagueness.
In Dominik Slezak, Guoyin Wang, Marcin S. Szczuka, Ivo Düntsch, Yiyu Yao, editors, Proceedings of the 10th International Conference on Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing (RSFDGrC), pages 541–550. In series: Lecture Notes in Artificial Intelligence #3641. Springer. ISBN: 3-540-28653-5.
DOI: 10.1007/11548669_56.

The relation of similarity is essential in understanding and developing frameworks for reasoning with vague and approximate concepts. There is a wide spectrum of choice as to what properties we associate with similarity and such choices determine the nature of vague and approximate concepts defined in terms of these relations. Additionally, robotic systems naturally have to deal with vague and approximate concepts due to the limitations in reasoning and sensor capabilities. Halpern [1] introduces the use of subjective and objective states in a modal logic formalizing vagueness and distinctions in transitivity when an agent reasons in the context of sensory and other limitations. He also relates these ideas to a solution to the Sorities and other paradoxes. In this paper, we generalize and apply the idea of similarity and tolerance spaces [2,3,4,5], a means of constructing approximate and vague concepts from such spaces and an explicit way to distinguish between an agent’s objective and subjective states. We also show how some of the intuitions from Halpern can be used with similarity spaces to formalize the above-mentioned Sorities and other paradoxes.

[55] Full text  Fredrik Heintz and Patrick Doherty. 2005.
A knowledge processing middleware framework and its relation to the JDL data fusion model.
In The 8th International Conference on Information Fusion,2005.

[54] Full text  Mariusz Wzorek and Patrick Doherty. 2005.
Reconfigurable path planning for an autonomous unmanned aerial vehicle.
In National Swedish Workshop on Autonomous Systems, SWAR 05,2005.

[53] Full text  Mariusz Wzorek and Patrick Doherty. 2005.
Preliminary report: Reconfigurable path planning for an autonomous unmanned aerial vehicle.
In Proceedings of the 24th Annual Workshop of the UK Planning and Scheduling Special Interest Group (PlanSIG).

[52] Patrick Doherty. 2005.
Knowledge representation and unmanned aerial vehicles.
In Proceedings of the IEEE/WIC/ACM International Conference on Intelligent Agent Technology (IAT), pages 9–16. IEEE Computer Society. ISBN: 0-7695-2416-8.
DOI: 10.1109/IAT.2005.93.

Knowledge representation technologies play a fundamental role in any autonomous system that includes deliberative capability and that internalizes models of its internal and external environments. Integrating both high- and low-end autonomous functionality seamlessly in autonomous architectures is currently one of the major open problems in robotics research. UAVs offer especially difficult challenges in comparison with ground robotic systems due to the often tight time constraints and safety considerations that must be taken into account. This article provides an overview of some of the knowledge representation technologies and deliberative capabilities developed for a fully deployed autonomous unmanned aerial vehicle system to meet some of these challenges.

[51] Full text  Fredrik Heintz and Patrick Doherty. 2005.
A Knowledge processing Middleware Framework and its Relation to the JDL Data Fusion model.
In SWAR 05,2005, pages 50–51.

[50] Full text  Fredrik Heintz and Patrick Doherty. 2005.
A Knowledge processing Middleware Framework and its Relation to the JDL Data Fusion model.
In 3rd joint SAIS-SSL event on Artificial Intelligence an Learning Systems,2005. Mälardalens University.

[49] Full text  Martin Magnusson, Patrick Doherty and Andrzej Szalas. 2005.
An Experimental Platform for Approximate Databases.
In 3rd joint SAIS-SSL event on Artificial Intelligence and Learning Systems,2005.

[48] Full text  Per Olof Pettersson and Patrick Doherty. 2005.
Probabilistic Roadmap Based Path Planning for an Autonomous Unmanned Helicopter.
In Peter Funk, Thorsteinn Rögnvaldsson and Ning Xiong, editors, Proceedings of the 3rd joint SAIS-SSLS event on Artificial Intelligence and Learning Systems (SAIS-SSLS). Mälardalen University.

The emerging area of intelligent unmanned aerialvehicle (UAV) research has shown rapid development in recentyears and offers a great number of research challenges for artificialintelligence. For both military and civil applications, thereis a desire to develop more sophisticated UAV platforms wherethe emphasis is placed on development of intelligent capabilities.Imagine a mission scenario where a UAV is supplied with a 3Dmodel of a region containing buildings and road structures andis instructed to fly to an arbitrary number of building structuresand collect video streams of each of the building’s respectivefacades. In this article, we describe a fully operational UAVplatform which can achieve such missions autonomously. Wefocus on the path planner integrated with the platform which cangenerate collision free paths autonomously during such missions.It is based on the use of probabilistic roadmaps. The path plannerhas been tested together with the UAV platform in an urbanenvironment used for UAV experimentation.

2004
[47] Full text  Fredrik Heintz and Patrick Doherty. 2004.
DyKnow: A Framework for Processing Dynamic Knowledge and Object Structures in Autonomous Systems.
In Proceedings of the Second Joint SAIS/SSLS Workshop.

[46] Full text  Patrick Doherty, Steven Kertes, Martin Magnusson and Andrzej Szalas. 2004.
Towards a logical analysis of biochemical pathways.
In José Júlio Alferes and João Alexandre Leite, editors, Proceedings of the 9th European Conference on Logics in Artificial Intelligence (JELIA), pages 667–679. In series: Lecture Notes in Computer Science #3229. Springer. ISBN: 978-3-540-23242-1.
DOI: 10.1007/978-3-540-30227-8_55.

Biochemical pathways or networks are generic representations used to model many different types of complex functional and physical interactions in biological systems. Models based on experimental results are often incomplete, e.g., reactions may be missing and only some products are observed. In such cases, one would like to reason about incomplete network representations and propose candidate hypotheses, which when represented as additional reactions, substrates, products, would complete the network and provide causal explanations for the existing observations. In this paper, we provide a logical model of biochemical pathways and show how abductive hypothesis generation may be used to provide additional information about incomplete pathways. Hypothesis generation is achieved using weakest and strongest necessary conditions which represent these incomplete biochemical pathways and explain observations about the functional and physical interactions being modeled. The techniques are demonstrated using metabolism and molecular synthesis examples.

[45] Full text  Patrick Doherty. 2004.
Advanced Research with Autonomous Unmanned Aerial Vehicles.
In Proceedings of the 9th International Conference on the Principles of Knowledge Representation and Reasoning, pages 731–732. AAAI Press. ISBN: 978-1-57735-199-3.

The emerging area of intelligent unmanned aerial vehicle (UAV) research has shown rapid development in recent years and offers a great number of research challenges for artificial intelligence and knowledge representation. For both military and civilian applications, there is a desire to develop more sophisticated UAV platforms where the emphasis is placed on intelligent capabilities and their integration in complex distributed software architectures. Such architectures should support the integration of deliberative, reactive and control functionalities in addition to the UAV’s integration with larger network centric systems. In my talk I will present some of the research and results from a long term basic research project with UAVs currently being pursued at Linköping University, Sweden. The talk will focus on knowledge representation techniques used in the project and the support for these techniques provided by the software architecture developed for our UAV platform, a Yamaha RMAX helicopter. Additional focus will be placed on some of the planning and execution monitoring functionality developed for our applications in the areas of traffic monitoring, surveying and photogrammetry and emergency services assistance.

[44] Full text  Per Olof Pettersson and Patrick Doherty. 2004.
Probabilistic Roadmap Based Path Planning for an Autonomous Unmanned Aerial Vehicle.
In ICAPS-04 Workshop on Connecting Planning Theory with Practice,2004, pages 49–55.

[43] Full text  Patrick Doherty, Patrik Haslum, Fredrik Heintz, Torsten Merz, Per Nyblom, Tommy Persson and Björn Wingman. 2004.
A Distributed Architecture for Autonomous Unmanned Aerial Vehicle Experimentation.
In 7th International Symposium on Distributed Autonomous Robotic Systems,2004. LAAS.

[42] Full text  Fredrik Heintz and Patrick Doherty. 2004.
Managing Dynamic Object Structures using Hypothesis Generation and Validation.
In AAAI Workshop on Anchoring Symbols to Sensor Data,2004, pages 54–62. AAAI Press.

[41] Full text  Fredrik Heintz and Patrick Doherty. 2004.
DyKnow: A Framework for Processing Dynamic Knowledge and Object Structures in Autonomous Systems.
In Barbara Dunin-Keplicz, Andrzej Jankowski, Andrzej Skowron, Marcin Szczuka, editors, Proceedings of the International Workshop on Monitoring, Security, and Rescue Techniques in Multi-Agent Systems (MSRAS), pages 479–492. In series: Advances in Soft Computing #28. Springer. ISBN: 978-3540232452.
DOI: 10.1007/3-540-32370-8_37.

Any autonomous system embedded in a dynamic and changing environment must be able to create qualitative knowledge and object structures representing aspects of its environment on the fly from raw or preprocessed sensor data in order to reason qualitatively about the environment. These structures must be managed and made accessible to deliberative and reactive functionalities which are dependent on being situationally aware of the changes in both the robotic agent’s embedding and internal environment. DyKnow is a software framework which provides a set of functionalities for contextually accessing, storing, creating and processing such structures. The system is implemented and has been deployed in a deliberative/reactive architecture for an autonomous unmanned aerial vehicle. The architecture itself is distributed and uses real-time CORBA as a communications infrastructure. We describe the system and show how it can be used in execution monitoring and chronicle recognition scenarios for UAV applications.

[40] Full text  Patrick Doherty, Steven Kertes, Martin Magnusson and Andrzej Szalas. 2004.
Towards a Logical Analysis of Biochemical Reactions (Extended abstract).
In Ramon López de Mántaras, Lorenza Saitta, editors, Proceedings of the 16th European Conference on Artificial Intelligence (ECAI), pages 997–998. IOS Press. ISBN: 1-58603-452-9.

We provide a logical model of biochemical reactions and show how hypothesis generation using weakest sufficient and strongest necessary conditions may be used to provide additional information in the context of an incomplete model of metabolic pathways.

[39] Full text  Patrick Doherty, Witold Lukaszewicz and Andrzej Szalas. 2004.
Approximate Databases and Query Techniques for Agents with Heterogenous Perceptual Capabilities.
In Proceedings of the 7th International Conference on Information Fusion, pages 175–182. ISIF. ISBN: 91-7056-115-X.

In this paper, we propose a framework that provides software and robotic agents with the ability to ask approximate questions to each other in the context of heterogeneous and contextually limited perceptual capabilities. The framework focuses on situations where agents have varying ability to perceive their environments. These limitations on perceptual capability are formalized using the idea of tolerance spaces. It is assumed that each agent has one or more approximate databases where approximate relations are represented using intuitions from rough set theory. It is shown how sensory and other limitations can be taken into account when constructing approximate databases for each respective agent. Complex relations inherit the approximativeness inherent in the sensors and primitive relations used in their definitions. Agents then query these databases and receive answers through the filters of their perceptual limitations as represented by tolerance spaces and approximate queries. The techniques used are all tractable.

[38] Full text  Patrick Doherty and Andrzej Szalas. 2004.
On the Correspondence between Approximations and Similarity.
In Shusaku Tsumoto, Roman Slowinski, Jan Komorowski and Jerzy W. Grzymala-Busse, editors, Proceedings of the International Conference on Rough Sets and Current Trends in Computing (RSCTC), pages 143–152. In series: Lecture Notes in Computer Science #3066. Springer.
DOI: 10.1007/978-3-540-25929-9_16.

This paper focuses on the use and interpretation of approximate databases where both rough sets and indiscernibility partitions are generalized and replaced by approximate relations and similarity spaces. Similarity spaces are used to define neighborhoods around individuals and these in turn are used to define approximate sets and relations. There is a wide spectrum of choice as to what properties the similarity relation should have and how this affects the properties of approximate relations in the database. In order to make this interaction precise, we propose a technique which permits specification of both approximation and similarity constraints on approximate databases and automatic translation between them. This technique provides great insight into the relation between similarity and approximation and is similar to that used in modal correspondence theory. In order to automate the translations, quantifier elimination techniques are used.

[37] Full text  Patrick Doherty, Witold Lukaszewicz and Andrzej Szalas. 2004.
Approximative Query Techniques for Agents with Heterogeneous Ontologies and Perceptive Capabilities.
In Didier Dubois, Christopher A. Welty, Mary-Anne Williams, editors, Proceedings of the 9th International Conference on the Principles of Knowledge Representation and Reasoning, pages 459–468. AAAI Press. ISBN: 978-1-57735-199-3.

In this paper, we propose a framework that provides software and robotic agents with the ability to ask approximate questions to each other in the context of heterogeneous ontologies and heterogeneous perceptive capabilities.The framework combines the use of logic-based techniques with ideas from approximate reasoning. Initial queries by an agent are transformed into approximate queries using weakest sufficient and strongest necessary conditions on the query and are interpreted as lower and upper approximations on the query. Once the base communication ability is provided, the framework is extended to situations where there is not only a mismatch between agent ontologies, but the agents have varying ability to perceive their environments. This will affect each agent’s ability to ask and interpret results of queries. Limitations on perceptive capability are formalized using the idea of tolerance spaces.

2003
[36] Full text  Erik Sandewall, Patrick Doherty, Oliver Lemon and Stanley Peters. 2003.
Words at the Right Time: Real-Time Dialogues with the WITAS Unmanned Aerial Vehicle.
In Proceedings of the 26th German Conference on Artificial Intelligence (KI), pages 52–63. In series: Lecture Notes in Computer Science #2821. Springer Verlag.
DOI: 10.1007/978-3-540-39451-8_5.

The WITAS project addresses the design of an intelligent, autonomous UAV (Unmanned Aerial Vehicle), in our case a helicopter. Its dialogue-system subprojects address the design of a deliberative system for natural-language and graphical dialogue with that robotic UAV. This raises new issues both for dialogue and for reasoning in real time. The following topics have been particularly important for us in various stages of the work in these subprojects: - spatiotemporal reference in the dialogue, including reference to past events and to planned or expected, future events - mixed initiative in the dialogue architecture of a complex system consisting of both dialogue-related components (speech, grammar, etc) and others (simulation, event recognition, interface to robot) and more recently as well - identification of a dialogue manager that is no more complex than what is required by the application - uniform treatment of different types of events, including the robot's own actions, observed events, communication events, and dialogue-oriented deliberation events - a logic of time, action, and spatiotemporal phenomena that facilitates the above. This paper gives a brief overview of the WITAS project as a whole, and then addresses the approaches that have been used and that are presently being considered in the work on two generations of dialogue subsystems.

[35] Full text  Patrick Doherty, Witold Lukaszewicz and Andrzej Szalas. 2003.
On mutual understanding among communicating agents.
In B. Dunin-Keplicz and R. Verbrugge, editors, Proceedings of the International Workshop on Formal Approaches to Multi-Agent Systems (FAMAS), pages 83–97.

[34] Full text  Patrick Doherty, Witold Lukaszewicz and Andrzej Szalas. 2003.
Tolerance Spaces and Approximative Representational Structures.
In Proceedings of the 26th German Conference on Artificial Intelligence (KI), pages 475–489. In series: Lecture Notes in Computer Science #2821. Springer.
DOI: 10.1007/978-3-540-39451-8_35.

In traditional approaches to knowledge representation, notions such as tolerance measures on data, distance between objects or individuals, and similarity measures between primitive and complex data structures are rarely considered. There is often a need to use tolerance and similarity measures in processes of data and knowledge abstraction because many complex systems which have knowledge representation components such as robots or software agents receive and process data which is incomplete, noisy, approximative and uncertain. This paper presents a framework for recursively constructing arbitrarily complex knowledge structures which may be compared for similarity, distance and approximativeness. It integrates nicely with more traditional knowledge representation techniques and attempts to bridge a gap between approximate and crisp knowledge representation. It can be viewed in part as a generalization of approximate reasoning techniques used in rough set theory. The strategy that will be used is to define tolerance and distance measures on the value sets associated with attributes or primitive data domains associated with particular applications. These tolerance and distance measures will be induced through the different levels of data and knowledge abstraction in complex representational structures. Once the tolerance and similarity measures are in place, an important structuring generalization can be made where the idea of a tolerance space is introduced. Use of these ideas is exemplified using two application domains related to sensor modeling and communication between agents.

[33] Patrick Doherty, Witold Lukaszewicz and Andrzej Szalas. 2003.
Information Granules for Intelligent Knowledge Structures.
In Guoyin Wang, Qing Liu, Yiyu Yao, Andrzej Skowron, editors, Proceedings of the 9th International Conference on Rough Sets, Fuzzy Sets, Data Mining and Granular Computing (RSFDGrC), pages 405–412. In series: Lecture Notes in Computer Science #2639. Springer. ISBN: 978-3-540-14040-5.
DOI: 10.1007/3-540-39205-X_68.

The premise of this paper is that the acquisition, aggregation, merging and use of information requires some new ideas, tools and techniques which can simplify the construction, analysis and use of what we call ephemeral knowledge structures. Ephemeral knowledge structures are used and constructed by granular agents. Each agent contains its own granular information structure and granular information structures of agents can be combined together. The main concept considered in this paper is an information granule. An information granule is a concise conceptual unit that can be integrated into a larger information infrastructure consisting of other information granules and dependencies between them. The novelty of this paper is that it provides a concise and formal definition of a particular view of information granule and its associated operators, as required in advanced knowledge representation applications.

2002
[32] Full text  Klas Nordberg, Patrick Doherty, Gunnar Farnebäck, Per-Erik Forssén, Gösta Granlund, Anders Moe and Johan Wiklund. 2002.
Vision for a UAV helicopter.
In International Conference on Intelligent Robots and Systems (IROS), Workshop on Aerial Robotics: Lausanne, Switzerland.

This paper presents and overview of the basic and applied research carried out by the Computer Vision Laboratory, Linköping University, in the WITAS UAV Project. This work includes customizing and redesigning vision methods to fit the particular needs and restrictions imposed by the UAV platform, e.g., for low-level vision, motion estimation, navigation, and tracking. It also includes a new learning structure for association of perception-action activations, and a runtime system for implementation and execution of vision algorithms. The paper contains also a brief introduction to the WITAS UAV Project.

[31] Full text  Patrick Doherty, Witold Lukaszewicz and Andrzej Szalas. 2002.
CAKE: A computer aided knowledge engineering technique.
In Frank van Harmelen, editor, Proceedings of the 15th European Conference on Artificial Intelligence,2002, pages 220–224. IOS Press.

Introduction: Logic engineering often involves the development of modeling tools and inference mechanisms (both standard and non-standard) which are targeted for use in practical applications where expressiveness in representation must be traded off for efficiency in use. Some representative examples of such applications would be the structuring and querying of knowledge on the semantic web, or the representation and querying of epistemic states used with softbots, robots or smart devices. In these application areas, declarative representations of knowledge enhance the functionality of such systems and also provide a basis for insuring the pragmatic properties of modularity and incremental composition. In addition, the mechanisms developed should be tractable, but at the same time, expressive enough to represent such aspects as default reasoning, or approximate or incomplete representations of the environments in which the entities in question are embedded or used, be they virtual or actual. [...]

[30] Full text  Per Andersson, Krzysztof Kuchcinski, Klas Nordberg and Patrick Doherty. 2002.
Integrating a computational model and a run time system for image processing on a UAV.
In Euromicro Symposium on Digital System Design (DSD), pages 102–109.
DOI: 10.1109/DSD.2002.1115357.

Recently substantial research has been devoted to Unmanned Aerial Vehicles (UAVs). One of a UAV's most demanding subsystem is vision. The vision subsystem must dynamically combine different algorithms as the UAVs goal and surrounding change. To fully utilize the available hardware, a run time system must be able to vary the quality and the size of regions the algorithms are applied to, as the number of image processing tasks changes. To allow this the run time system and the underlying computational model must be integrated. In this paper we present a computational model suitable for integration with a run time system. The computational model is called Image Processing Data Flow Graph (IP-DFG). IP-DFG has been developed for modeling of complex image processing algorithms. IP-DFG is based on data flow graphs, but has been extended with hierarchy and new rules for token consumption, which makes the computational model more flexible and more suitable for human interaction. In this paper we also show that IP-DFGs are suitable for modelling expressions, including data dependent decisions and iterations, which are common in complex image processing algorithms.

2001
[29] Full text  Fredrik Heintz and Patrick Doherty. 2001.
Chronicle Recognition in the WITAS UAV Project: A Preliminary Report.
In Proceedings of the Swedish AI Society Workshop.

This paper describes the chronicle recognition problem and reports its status in the WITAS UAV project. We describe how we use the IxTeT chronicle recognition system to define chronicles (scenarios or situations), like a vehicle passing another vehicle, and how it is incorporated in the WITAS architecture. We also discuss known problems with the current system and possible directions of future research.

[28] Full text  Patrick Doherty, Witold Lukaszewicz and Andrzej Szalas. 2001.
Computing strongest necessary and weakest sufficient conditions of first-order formulas.
In 17th International Joint Conference on Artificial Intelligence,2001, pages 145–151. Morgan Kaufmann Publishers Inc.. ISBN: 1-55860-812-5, 978-1-558-60812-2.

A technique is proposed for computing the weakest sufficient (wsc) and strongest necessary (snc) conditions for formulas in an expressive fragment of first-order logic using quantifier elimination techniques. The efficacy of the approach is demonstrated by using the techniques to compute snc's and wsc's for use in agent communication applications, theory approximation and generation of abductive hypotheses. Additionally, we generalize recent results involving the generation of successor state axioms in the propositional situation calculus via snc's to the first-order case. Subsumption results for existing approaches to this problem and a re-interpretation of the concept of forgetting as a process of quantifier elimination are also provided.

2000
[27] Full text  Jonas Kvarnström, Patrick Doherty and Patrik Haslum. 2000.
Extending TALplanner with concurrency and resources.
In Proceedings of the 14th European Conference on Artificial Intelligence (ECAI), pages 501–505. In series: Frontiers in Artificial Intelligence and Applications #54. IOS Press. ISBN: 4274903885, 1586030132.
Link: http://swepub.kb.se/bib/swepub:oai:DiVA....

We present TALplanner, a forward-chaining planner based on the use of domain-dependent search control knowledge represented as temporal formulas in the Temporal Action Logic (TAL). TAL is a narrative based linear metric time logic used for reasoning about action and change in incompletely specified dynamic environments. TAL is used as the formal semantic basis for TALplanner, where a TAL goal narrative with control formulas is input to TALplanner which then generates a TAL narrative that entails the goal formula. We extend the sequential version of TALplanner, which has previously shown impressive performance on standard benchmarks, in two respects: 1) TALplanner is extended to generate concurrent plans, where operators have varied durations and internal state; and 2) the expressiveness of plan operators is extended for dealing with several different types of resources. The extensions to the planner have been implemented and concurrent planning with resources is demonstrated using an extended logistics benchmark.

[26] Full text  Patrick Doherty, Witold Lukaszewicz and Andrzej Szalas. 2000.
Efficient reasoning using the local closed-world assumption.
In Proceedings of the 9th International Conference on Artificial Intelligence: Methodology, Systems and Applications (AIMSA), pages 49–58. In series: Lecture Notes in Computer Science #1904. Springer Berlin/Heidelberg. ISBN: 978-3-540-41044-7, 978-3-540-45331-4.
DOI: 10.1007/3-540-45331-8_5.

We present a sound and complete, tractable inference method for reasoning with localized closed world assumptions (LCWA’s) which can be used in applications where a reasoning or planning agent can not assume complete information about planning or reasoning states. This <em>Open World Assumption</em> is generally necessary in most realistic robotics applications. The inference procedure subsumes that described in Etzioni et al [9], and others. In addition, it provides a great deal more expressivity, permitting limited use of negation and disjunction in the representation of LCWA’s, while still retaining tractability. The ap- proach is based on the use of circumscription and quantifier elimination techniques and inference is viewed as querying a deductive database. Both the preprocessing of the database using circumscription and quan- tifier elimination, and the inference method itself, have polynomial time and space complexity.

[25] Full text  Patrick Doherty, Gösta Granlund, Krzysztof Kuchcinski, Erik Johan Sandewall, Klas Nordberg, Erik Skarman and Johan Wiklund. 2000.
The WITAS unmanned aerial vehicle project.
In Werner Horn, editor, Proceedings of the 14th European Conference on Artificial Intelligence (ECAI), pages 747–755. IOS Press. ISBN: 1-58603-013-2, 4-274-90388-5.
Link: http://www2.cvl.isy.liu.se/ScOut/Publica...

The purpose of this paper is to provide a broad overview of the WITAS Unmanned Aerial Vehicle Project. The WITAS UAV project is an ambitious, long-term basic research project with the goal of developing technologies and functionalities necessary for the successful deployment of a fully autonomous UAV operating over diverse geographical terrain containing road and traffic networks. Theproject is multi-disciplinary in nature, requiring many different research competences, and covering a broad spectrum of basic research issues, many of which relate to current topics in artificial intelligence. A number of topics considered are knowledge representation issues, active vision systems and their integration with deliberative/reactive architectures, helicopter modeling and control, ground operator dialogue systems, actual physical platforms, and a number of simulation techniques.

[24] Full text  Gösta Granlund, Klas Nordberg, Johan Wiklund, Patrick Doherty, Erik Skarman and Erik Sandewall. 2000.
WITAS: An Intelligent Autonomous Aircraft Using Active Vision.
In Proceedings of the UAV 2000 International Technical Conference and Exhibition (UAV). Euro UVS.
fulltext:preprint: http://liu.diva-portal.org/smash/get/div...

The WITAS Unmanned Aerial Vehicle Project is a long term basic research project located at Linköping University (LIU), Sweden. The project is multi-disciplinary in nature and involves cooperation with different departments at LIU, and a number of other universities in Europe, the USA, and South America. In addition to academic cooperation, the project involves collaboration with a number of private companies supplying products and expertise related to simulation tools and models, and the hardware and sensory platforms used for actual flight experimentation with the UAV. Currently, the project is in its second phase with an intended duration from 2000-2003.This paper will begin with a brief overview of the project, but will focus primarily on the computer vision related issues associated with interpreting the operational environment which consists of traffic and road networks and vehicular patterns associated with these networks.

1999
[23] Patrick Doherty, Witold Lukaszewicz and E. Madalin´ska-Bugaj. 1999.
Computing MPMA updates using dijkstra's semantics.
In 12th International Symposium on Methodologies for Intelligent Systems,1999. Springer.

[22] Full text  Patrick Doherty and Jonas Kvarnström. 1999.
TALplanner: An empirical investigation of a temporal logic-based forward chaining planner.
In Clare Dixon, Michael Fisher, editors, 6th International Workshop on Temporal Representation and Reasoning (TIME-99). IEEE Computer Society. ISBN: 0-7695-0173-7.

We present a new forward chaining planner, TALplanner, based on ideas developed by Bacchus and Kabanza, where domain-dependent search control knowledge represented as temporal formulas is used to effectively control forward chaining. Instead of using a linear modal tense logic as with Bacchus and Kabanza, we use TAL, a narrative-based linear temporal logic used for reasoning about action and change in incompletely specified dynamic environments. Two versions of TALplanner are considered, TALplan/modal which is based on the use of emulated modal formulas and a progression algorithm, and TALplan/non-modal which uses neither modal formulas nor a progression algorithm. For both versions of TALplanner and for all tested domains, TALplanner is shown to be considerably faster and requires less memory. The TAL versions also permit the representation of durative actions with internal state.

[21] John-Jules Meyer and Patrick Doherty. 1999.
Preferential action semantics (preliminary report).
In Formal Models of Agents: ESPRIT Project Modelage Final Workshop Selected Papers, pages 187–201. In series: Lecture Notes in Artificial Intelligence #1760. Springer. ISBN: 3-540-67027-0.
DOI: 10.1007/3-540-46581-2_13.
Note: Preliminary report

In this paper, we propose a new way of considering reasoning about action and change. Rather than placing a preferential structure onto the models of logical theories, we place such a structure directly on the semantics of the actions involved. In this way, we obtain a preferential semantics of actions by means of which we can not only deal with several of the traditional problems in this area such as the frame and ramification problems, but can generalize these solutions to a context which includes both nondeterministic and concurrent actions. In fact, the net result is an integration of semantical and verificational techniques from the paradigm of imperative and concurrent programs in particular, as known from traditional programming, with the AI perspective. In this paper, the main focus is on semantical (i.e. model theoretical) issues rather than providing a logical calculus, which would be the next step in the endeavor.

1998
[20] Lars Karlsson, Joakim Gustafsson and Patrick Doherty. 1998.
Delayed effects of actions.
In Proceedings of the 13th European Conference on Artificial Intelligence (ECAI), pages 542–546. John Wiley & Sons. ISBN: 978-0471984313.

[19] Full text  Patrick Doherty, Witold Lukaszewicz and Ewa Madalinska-Bugaj. 1998.
The PMA and relativizing change for action update.
In Proceedings of the 6th International Conference on Principles of Knowledge Representation and Reasoning (KR), pages 258–269. Morgan Kaufmann Publishers.

Using intuitions from the temporal reasoning community, we provide a generalization of the PMA, called the modified PMA (MPMA), which permits the representation of disjunctive updates and the use of integrity constraints interpreted as causal constraints. In addition, we provide a number of syntactic characterizations of the MPMA, one of which is constructed by mapping an MPMA update of a knowledge base into a temporal narrative in a simple temporal logic (STL). The resulting representation theorem provides a basis for computing entailments of the MPMA and could serve as a basis for further generalization of the belief update approach for reasoning about action and change.

[18] Full text  Patrick Doherty and Jonas Kvarnström. 1998.
Tackling the qualification problem using fluent dependency constraints.
In Lina Khatib, Robert Morris, editors, Proceedings of the 5th International Workshop on Temporal Representation and Reasoning (TIME-98). IEEE Computer Society. ISBN: 0-8186-8473-9.
Note: Preliminary report

The use of causal rules or fluent dependency constraints has proven to provide a versatile means of dealing with the ramification problem. In this paper we show how fluent dependency constraints together with the use of durational fluents can be used to deal with problems associated with action qualification. We provide both a \emph{weak} and \emph{strong} form of qualification and demonstrate the approach using an action scenario which combines solutions to the frame, ramification and qualification problems in the context of actions with duration, concurrent actions, non-deterministic actions and the use of both boolean and non-boolean fluents. The circumscription policy used for the combined problems is reducible to the 1st-order case. In addition, we demonstrate the use of a research tool VITAL, for querying and visualizing action scenarios.

1996
[17] Full text  Joakim Gustafsson and Patrick Doherty. 1996.
Embracing occlusion in specifying the indirect effects of actions.
In Luigia Carlucci Aiello, Jon Doyle, Stuart C. Shapiro, editors, Proceedings of the 5th International Conference on Principles of Knowledge Representation and Reasoning, pages 87–98. Morgan Kaufmann Publishers. ISBN: 1-55860-421-9.

In this paper, we extend PMON, a logic for reasoning about action and change, with causal rules which are used to specify the indirect effects of actions The extension, called PMON(RCs), has the advantage of using explicit time, includes actions with durations, nondeterministic actions, allows partial specification of the timing and order of actions and has been assessed correct for at least the K-IA class of action scenarios within the Features and Fluents framework Most importantly, the circumscription policy used is easily shown to be reducible to the firstorder case which insures that standard theorem proving techniques and their optimizations may be used to compute entailment In addition, we show how the occlusion concept previously used to deal with duration and nondeterministic actions proves to be equally versatile in representing causal constraints and delayed effects of actions We also discuss related work and consider the strong correspondence between our work and recent work by Lin, who uses a Cause predicate to specify indirect effects similar to our use of Occlude in PMON, and a minimization policy related to that used in PMON.

[16] Full text  Patrick Doherty, Witold Lukaszewicz and Andrzej Szalas. 1996.
Explaining explanation closure.
In Zbigniew W. Ras, Maciek Michalewicz, editors, Proceedings of the 9th International Symposium on Methodologies for Intelligent Systems,1996, pages 521–530. In series: Lecture Notes in Computer Science #1079. Springer Berlin/Heidelberg. ISBN: 3-540-61286-6.
DOI: 10.1007/3-540-61286-6_176.

Recently, Haas, Schubert, and Reiter, have developed an alternative approach to the frame problem which is based on the idea of using <em>explanation closure axioms</em>. The claim is that there is a monotonic solution for characterizing nonchange in serial worlds with fully specified actions, where one can have both a succinct representation of frame axioms and an effective proof theory for the characterization. In the paper, we propose a circumscriptive version of explanation closure, PMON, that has an effective proof theory and works for both context dependent and nondeterministic actions. The approach retains representational succinctness and a large degree of elaboration tolerance, since the process of generating closure axioms is fully automated and is of no concern to the knowledge engineer. In addition, we argue that the monotonic/nonmonotonic dichotomy proposed by others is not as sharp as previously claimed and is not fully justified.

[15] Full text  Patrick Doherty, Witold Lukaszewicz and Andrzej Szalas. 1996.
General domain circumscription and its first-order reduction.
In Dov Gabbay, Hans Olbach, editors, Proceedings of the 1st International Conference on Formal and Applied Practical Reasoning (FAPR), pages 93–109. In series: Lecture Notes in Computer Science #1085. Springer Berlin/Heidelberg. ISBN: 978-3-540-61313-8.
DOI: 10.1007/3-540-61313-7_65.

We first define general domain circumscription (GDC) and provide it with a semantics. GDC subsumes existing domain circumscription proposals in that it allows varying of arbitrary predicates, functions, or constants, to maximize the minimization of the domain of a theory We then show that for the class of semi-universal theories without function symbols, that the domain circumscription of such theories can be constructively reduced to logically equivalent first-order theories by using an extension of the DLS algorithm, previously proposed by the authors for reducing second-order formulas. We also isolate a class of domain circumscribed theories, such that any arbitrary second-order circumscription policy applied to these theories is guaranteed to be reducible to a logically equivalent first-order theory. In the case of semi-universal theories with functions and arbitrary theories which are not separated, we provide additional results, which although not guaranteed to provide reductions in all cases, do provide reductions in some cases. These results are based on the use of fixpoint reductions.

1995
[14] Full text  Patrick Doherty, Witold Lukaszewicz and Andrzej Szalas. 1995.
Computing circumscription revisited.
In Proceedings of the 14th International Joint Conference on Artificial Intelligence (IJCAI), pages 1502–1508. ISBN: 978-1558603639.
Note: Volume 2. Preliminary report

[13] Patrick Doherty and P. Peppas. 1995.
A comparison between two approaches to ramification: PMON(R) and AR0.
In 8th Australian Joint Conference on Artificial Intelligence,1995.
Note: World Scientific

1994
[12] Patrick Doherty and Witold Lukaszewicz. 1994.
Circumscribing features and fluents. A fluent logic for reasoning about action and change.
In 8th International Symposium on Methodologies for Intelligent Systems,1994. Springer Verlag.

[11] Patrick Doherty. 1994.
Reasoning about action and change using occlusion.
In 11th European Conference on Artificial Intelligence,1994. John Wiley and Sons.

1992
[10] Patrick Doherty and Witold Lukaszewicz. 1992.
Defaults as first-class citizens.
In Proceedings of the 22nd International Symposium on Multiple-Valued Logic (SMVL), pages 146–154. In series: Proceedings of the International Symposium on Multiple Valued Logic #??. IEEE Computer Society. ISBN: 0-8186-2680-1.

A nonmonotonic logic with explicit defaults, NML3, is presented. It is characterized by the following features: (1) the use of the strong Kleene three-valued logic as a basis; (2) the addition of an explicit default operator which enables distinguishing tentative conclusions from ordinary conclusions in the object language; and (3) the use of the idea of preferential entailment to generate nonmonotonic behavior. The central feature of the formalism, the use of an explicit default operator with a model-theoretic semantics based on the notion of a partial interpretation, distinguishes NML3 from most previous formalisms. By capitalizing on the distinction between tentative and ordinary conclusions, NML3 provides increased expressibility in comparison to many of the standard nonmonotonic formalisms and greater flexibility in the representation of subtle aspects of default reasoning. This is shown through examples.

[9] Patrick Doherty and Witold Lukaszewicz. 1992.
FONML3 - A first-order non-monotonic logic with explicit defaults.
In European Conference on Artificial Intelligence, ECAI-92,1992. John Wiley and Sons.

[8] Patrick Doherty, Dimiter Driankov and H. Hellendoorn. 1992.
Fuzzy if-then-unless rules and their implementation.
In International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems, IPMU92,1992. Springer.

[7] Patrick Doherty, Dimiter Driankov and A. Tsoukias. 1992.
Partial logics and partial preferences.
In International Conference on Economics/Management and Information Technology,1992.

1991
[6] Patrick Doherty and Dimiter Driankov. 1991.
A non-monotonic fuzzy logic.
In International Fuzzy Systems Association, Fourth World Congress,1991.

[5] Patrick Doherty. 1991.
A constraint-based approach to proof procedures for multi-valued logics.
In Proceedings of the 1st World Conference on Fundamentals of Artificial Intelligence (WOCFAI). Springer.

1990
[4] Patrick Doherty. 1990.
NME - A three-valued non-monotonic formalism.
In Proceedings of the 5th International Symposium on Methodologies for Intelligent Systems (ISMIS).
Note: Preliminary report

[3] Patrick Doherty. 1990.
NM3 - A three-valued cumulative non-monotonic formalism.
In Jan van Eijck, editor, Logics in AI, European Workshop (JELIA), pages 196–211. In series: Lecture Notes in Artificial Intelligence #478. Springer Berlin/Heidelberg. ISBN: 978-3-540-53686-4.
DOI: 10.1007/BFb0018442.

In this paper, we propose a formalization of non-monotonic reasoning using a three-valued logic based on the strong definitions of Kleene. We start by extending Kleene's three-valued logic with an \"external negation\" connective where ~ alpha is true when alpha is false or unknown. In addition, a default operator D is added where D alpha is interpreted as \"alpha is true by default\". The addition of the default operator increases the expressivity of the language, where statements such as \"alpha is not a default\" are directly representable. The logic has an intuitive model theoretic semantics without any appeal to the use of a fixpoint semantics for the default operator. The semantics is based on the notion of preferential entailment, where a set of sentences Gamma preferentially entails a sentence alpha, if and only if a preferred set of the models of Gamma are models of alpha. We also show that the logic belongs to the class of cumulative non-monotonic formalisms which are a subject of current interest.

1989
[2] Patrick Doherty. 1989.
A correspondence between inheritance hierarchies and a logic of preferential entailment.
In M. L. Emrich, M. S. Pfeifer, M. Hadzikadic, and Z. W. Ras, editors, Proceedings of the 4th International Symposium on Methodologies for Intelligent Systems (ISMIS). University of North Carolina Press.

[1] Patrick Doherty. 1989.
A semantics for inheritance hierarchies with exceptions using a logic of preferential entailment.
In Proceedings of the 2nd Scandinavian Conference on Artificial Intelligence (SCAI). IOS Press.