Automated Planning and Diagnosis
A long term
unmanned aerial vehicle (UAV) research projects provides one important
application domain for our research in planning.
troubleshooting of complex systems uses heavy trucks as an application
The Automated Planning and Diagnosis (APD) group is part of the Knowledge Processing Laboratory
(KPLAB) in the Artificial Intelligence
and Integrated Computer Systems (AIICS) Division at the Department
of Computer and Information Science at Linköping
Our research focuses on the pragmatic use of
automated planning and diagnosis techniques to solve real-world problems. We view
task planning as a central component of a solution that also involves essential
tasks such as information gathering, motion planning, plan execution, execution
monitoring, and interaction with human operators through mixed initiative
interfaces. Within this larger context, areas of specific long-term interest
include the following:
- Studying the integration and interaction between different aspects of the
planning and execution process, including the combination of task planning and
motion planning as well as the use of task planning in combination with plan
execution mechanisms, execution monitoring systems, and failure diagnosis /
- Generating plans for multiple agents and cooperative systems,
including delegation of subplans or subgoals and the use of distributed planning.
- Increasing the expressivity of plan representation languages and planners
for these languages in order to facilitate the specification of planning domains,
allow richer constraints on valid solutions, and make full use of available
- Handling uncertainty and incomplete information, both in terms of
timing and in terms of knowledge about the world in which an agent operates.
- Improving planning performance, both through purely algorithmic
improvements and through allowing new forms of domain information to be specified
and taken advantage of during the planning process.
- Studying the use of planning for diagnosis and troubleshooting, where
planning techniques are used to determine which steps to take to gather the
necessary information and to repair a system or otherwise recover from failures.
Most of our research is grounded in the pragmatic requirements of the following
concrete application domains:
- Mission planning for unmanned aerial vehicles. Together with other groups
at AIICS, we are involved
in a long-term research endeavor involving the design, specification and
implementation of autonomous architectures for intelligent
unmanned aircraft systems. Applications of such systems include traffic
surveillance and emergency services assistance. We currently use two Yamaha
RMAX helicopters as well as two micro UAVs (MAVs), and several small quad-rotor
UAVs have recently been acquired for further experimentation.
- Diagnosis and troubleshooting of complex systems. In close cooperation
with Scania AB, we are applying automated
planning techniques to incremental
diagnosis and troubleshooting for complex systems such as heavy trucks. The
need to balance the cost of testing against the cost of potentially replacing
non-faulty components can be modeled as an interesting form of probabilistic
planning problem, where the aim is to generate a repair plan with minimal
- Computer games. Computer games can provide a natural environment in which
to apply epistemic reasoning, where agents must generate plans given incomplete
information and plan for knowledge acquisition. They can also provide a
suitable testing ground for planning in the presence of agents that cannot be
completely controlled by the planner, aiding research in the areas of
cooperation and delegation. A small dialog-based adventure game is currently
used as one method for validating research in the Logical Agents project.