AIICS

Mattias Tiger

Conference and Workshop Publications

Show abstracts (where available) BibTeX entries
2023
[13] Mattias Tiger, David Bergström, Simon Wijk Stranius, Evelina Holmgren, Daniel de Leng and Fredrik Heintz. 2023.
On-Demand Multi-Agent Basket Picking for Shopping Stores.
In 2023 IEEE International Conference on Robotics and Automation (ICRA), pages 5793–5799. IEEE. ISBN: 9798350323658, 9798350323665.
DOI: 10.1109/ICRA48891.2023.10160398.
Note: Funding: Wallenberg AI, Autonomous Systems and Software Program (WASP) - Knut and Alice Wallenberg Foundation; National Graduate School in Computer Science (CUGS), Sweden; Excellence Center at Linkoping-Lund for Information Technology (ELLIIT); Knut and Alice Wallenberg Foundation [KAW 2019.0350]; TAILOR Project - EU Horizon 2020 research and innovation programme [952215]
fulltext:postprint: https://liu.diva-portal.org/smash/get/di...
2022
[12] Daniel Engelsons, Mattias Tiger and Fredrik Heintz. 2022.
Coverage Path Planning in Large-scale Multi-floor Urban Environments with Applications to Autonomous Road Sweeping.
In 2022 International Conference on Robotics and Automation (ICRA), pages 3328–3334. Institute of Electrical and Electronics Engineers (IEEE). ISBN: 9781728196817, 9781728196824.
DOI: 10.1109/ICRA46639.2022.9811941.
Note: Funding: 10.13039/501100004063-Knut and Alice Wallenberg Foundation (Grant Number: KAW 2019.0350)
fulltext:postprint: https://liu.diva-portal.org/smash/get/di...
2020
[11] Fredrik Präntare, Mattias Tiger, David Bergström, Herman Appelgren and Fredrik Heintz. 2020.
Towards Utilitarian Combinatorial Assignment with Deep Neural Networks and Heuristic Algorithms.
In .
[10] Full text  Mattias Tiger and Fredrik Heintz. 2020.
Spatio-Temporal Learning, Reasoning and Decision-Making with Robot Safety Applications: PhD Research Project Extended Abstract.
In Fredrik Johansson, editor, Proceedings of the 32nd annual workshop of the Swedish Artificial Intelligence Society (SAIS 2020).
2019
[9] Full text  David Bergström, Mattias Tiger and Fredrik Heintz. 2019.
Bayesian optimization for selecting training and validation data for supervised machine learning.
In 31st annual workshop of the Swedish Artificial Intelligence Society (SAIS 2019), Umeå, Sweden, June 18-19, 2019..
2018
[8] Full text  Olov Andersson, Oskar Ljungqvist, Mattias Tiger, Daniel Axehill and Fredrik Heintz. 2018.
Receding-Horizon Lattice-based Motion Planning with Dynamic Obstacle Avoidance.
In 2018 IEEE Conference on Decision and Control (CDC), pages 4467–4474. In series: Conference on Decision and Control (CDC) #2018. Institute of Electrical and Electronics Engineers (IEEE). ISBN: 9781538613955, 9781538613948, 9781538613962.
DOI: 10.1109/CDC.2018.8618964.
Note: This work was partially supported by FFI/VINNOVA, the Wallenberg Artificial Intelligence, Autonomous Systems and Software Program (WASP) funded by Knut and Alice Wallenberg Foundation, the Swedish Foundation for Strategic Research (SSF) project Symbicloud, the ELLIIT Excellence Center at Linköping-Lund for Information Technology, Swedish Research Council (VR) Linnaeus Center CADICS, and the National Graduate School in Computer Science, Sweden (CUGS).
fulltext:postprint: http://liu.diva-portal.org/smash/get/div...
[7] Full text  Mattias Tiger and Fredrik Heintz. 2018.
Gaussian Process Based Motion Pattern Recognition with Sequential Local Models.
In 2018 IEEE Intelligent Vehicles Symposium (IV), pages 1143–1149. In series: IEEE Intelligent Vehicles Symposium #2018. Institute of Electrical and Electronics Engineers (IEEE). ISBN: 9781538644522, 9781538644515, 9781538644539.
DOI: 10.1109/IVS.2018.8500676.
fulltext:postprint: http://liu.diva-portal.org/smash/get/div...
[6] Full text  Daniel de Leng, Mattias Tiger, Mathias Almquist, Viktor Almquist and Niklas Carlsson. 2018.
Second Screen Journey to the Cup: Twitter Dynamics during the Stanley Cup Playoffs.
In Proceedings of the 2nd Network Traffic Measurement and Analysis Conference (TMA), pages 1–8. ISBN: 978-3-903176-09-6, 978-1-5386-7152-8.
DOI: 10.23919/TMA.2018.8506531.
Note: Funding agencies:  Swedish Research Council (VR); National Graduate School in Computer Science, Sweden (CUGS) Swedish Research Council (VR); National Graduate School in Computer Science, Sweden (CUGS)
2016
[5] Full text  Mattias Tiger and Fredrik Heintz. 2016.
Stream Reasoning using Temporal Logic and Predictive Probabilistic State Models.
In 23nd International Symposium on Temporal Representation and Reasoning (TIME), 2016. IEEE Computer Society.
Note: Presented at the 23nd International Symposium on Temporal Representation and Reasoning (TIME) at the Technical University of Denmark (DTU), Denmark, the 19th October 2016.
[4] Full text  Mattias Tiger and Fredrik Heintz. 2016.
Stream Reasoning using Temporal Logic and Predictive Probabilistic State Models.
In 23nd International Symposium on Temporal Representation and Reasoning (TIME), 2016, pages 196–205. IEEE Computer Society. ISBN: 978-1-5090-3825-1.
DOI: 10.1109/TIME.2016.28.
Note: Presented at the 23nd International Symposium on Temporal Representation and Reasoning (TIME) at the Technical University of Denmark (DTU), Denmark, the 19th October 2016.
fulltext:postprint: http://liu.diva-portal.org/smash/get/div...
2015
[3] Full text  Mattias Tiger and Fredrik Heintz. 2015.
Towards Unsupervised Learning, Classification and Prediction of Activities in a Stream-Based Framework.
In Proceedings of the Thirteenth Scandinavian Conference on Artificial Intelligence (SCAI), pages 147–156. In series: Frontiers in Artificial Intelligence and Applications #278. IOS Press. ISBN: 978-1-61499-588-3.
DOI: 10.3233/978-1-61499-589-0-147.
länk till artikeln: https://www.ida.liu.se/divisions/aiics/p...
[2] Full text  Mattias Tiger and Fredrik Heintz. 2015.
Online Sparse Gaussian Process Regression for Trajectory Modeling.
In 18th International Conference on Information Fusion (Fusion), 2015, pages 782–791. IEEE. ISBN: 9780982443866, 9780982443873.
Publisher's full text: https://ieeexplore.ieee.org/document/726...
2014
[1] Full text  Mattias Tiger and Fredrik Heintz. 2014.
Towards Learning and Classifying Spatio-Temporal Activities in a Stream Processing Framework.
In Ulle Endriss and João Leite, editors, STAIRS 2014: Proceedings of the 7th European Starting AI Researcher Symposium, pages 280–289. In series: Frontiers in Artificial Intelligence and Applications #264. IOS Press. ISBN: 978-1-61499-420-6, 978-1-61499-421-3.
DOI: 10.3233/978-1-61499-421-3-280.
Fulltext: https://doi.org/10.3233/978-1-61499-421-...
Ebook: STAIRS 2014: http://ebooks.iospress.nl/volume/stairs-...
fulltext:print: http://liu.diva-portal.org/smash/get/div...