I am Deputy Head of the Reasoning and Learning (ReaL) Lab and actively involved in national and international initiatives on trustworthy AI and autonomous systems.
Mattias Tiger
Assistant Professor
Artificial intelligence is about automated problem solving. I develop AI and autonomous systems that operate reliably over time, handling uncertainty and change while remaining safe and trustworthy in real-world environments.
Artificial Intelligence – from theory to real-world systems
I am an AI researcher at Linköping University, working on safe, robust, and trustworthy AI and autonomous systems. My research focuses on combining learning and reasoning to enable AI systems that can operate reliably in complex, dynamic, real-world environments.
I am Deputy Head of the Reasoning and Learning (ReaL) Lab and actively involved in national and international initiatives on trustworthy AI and autonomous systems.
Research
Coverage Path Planning in Urban Environments with Applications to Autonomous Road Sweeping
2022 IEEE International Conferance on Robotics and Automation (ICRA)
Enhancing Lattice-based Motion Planning with Introspective Learning and Reasoning
2021 IEEE Robotics and Automation Letters (RA-L), 2021 IEEE International Conferance on Robotics and Automation (ICRA)
Efficient Autonomous Exploration Planning of Large Scale 3D-Environments
2019 IEEE Robotics and Automation Letters (RA-L), 2019 IEEE International Conferance on Robotics and Automation (ICRA)
Receding-Horizon Lattice-based Motion Planning with Dynamic Obstacle Avoidance
This video presents simulation results for the paper with the title "Receding-Horizon Lattice-based Motion Planning with Dynamic Obstacle Avoidance". The paper was in the proceedings of the 57th IEEE Conference on Decision and Control 2018. Contributors: Oskar Ljungqvist, Mattias Tiger, Olov Andersson, Daniel Axehill, Fredrik Heintz.
Publications
2025
Safe Lattice Planning for Motion Planning with Dynamic Obstacles
IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), p. 9287-9294
(Conference paper)
https://dx.doi.org/10.1109/IROS60139.2025.11247023
2024
Enhancing Safety via Deep Reinforcement Learning in Trajectory Planning for Agile Flights in Unknown Environments
2024 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS, IROS 2024, p. 3076-3083
(Conference paper)
https://dx.doi.org/10.1109/IROS58592.2024.10801910
Autonomous 3D Exploration in Large-Scale Environments with Dynamic Obstacles
2024 IEEE International Conference on Robotics and Automation (ICRA), p. 2389-2395
(Conference paper)
https://dx.doi.org/10.1109/ICRA57147.2024.10610996
Autonomous 3D Exploration in Large-Scale Environments with Dynamic Obstacles
(Conference paper)
2023
On-Demand Multi-Agent Basket Picking for Shopping Stores
2023 IEEE International Conference on Robotics and Automation (ICRA), p. 5793-5799
(Conference paper)
https://dx.doi.org/10.1109/ICRA48891.2023.10160398
2022
Safety-Aware Autonomous Systems: Preparing Robots for Life in the Real World
(Doctoral thesis, monograph)
https://dx.doi.org/10.3384/9789179295028
Coverage Path Planning in Large-scale Multi-floor Urban Environments with Applications to Autonomous Road Sweeping
2022 International Conference on Robotics and Automation (ICRA), p. 3328-3334
(Conference paper)
https://dx.doi.org/10.1109/ICRA46639.2022.9811941
2021
Enhancing Lattice-Based Motion Planning With Introspective Learning and Reasoning
IEEE Robotics and Automation Letters, Vol. 6, p. 4385-4392
(Article in journal)
https://dx.doi.org/10.1109/LRA.2021.3068550
2020
Towards Utilitarian Combinatorial Assignment with Deep Neural Networks and Heuristic Algorithms
Trustworthy AI - Integrating Learning, Optimization and Reasoning: First International Workshop, TAILOR 2020, Virtual Event, September 4–5, 2020, Revised Selected Papers, p. 104-111
(Conference paper)
https://dx.doi.org/10.1007/978-3-030-73959-1_10
Spatio-Temporal Learning, Reasoning and Decision-Making with Robot Safety Applications: PhD Research Project Extended Abstract
Proceedings of the 32nd annual workshop of the Swedish Artificial Intelligence Society (SAIS 2020)
(Conference paper)
Incremental Reasoning in Probabilistic Signal Temporal Logic
International Journal of Approximate Reasoning, Vol. 119, p. 325-352, Article j.ijar.2020.01.009
(Article in journal)
https://dx.doi.org/10.1016/j.ijar.2020.01.009
2019
Bayesian optimization for selecting training and validation data for supervised machine learning
31st annual workshop of the Swedish Artificial Intelligence Society (SAIS 2019), Umeå, Sweden, June 18-19, 2019.
(Conference paper)
Efficient Autonomous Exploration Planning of Large Scale 3D-Environments
IEEE Robotics and Automation Letters, Vol. 4, p. 1699-1706
(Article in journal)
https://dx.doi.org/10.1109/LRA.2019.2897343
2018
Receding-Horizon Lattice-based Motion Planning with Dynamic Obstacle Avoidance
2018 IEEE Conference on Decision and Control (CDC), p. 4467-4474
(Conference paper)
https://dx.doi.org/10.1109/CDC.2018.8618964
Gaussian Process Based Motion Pattern Recognition with Sequential Local Models
2018 IEEE Intelligent Vehicles Symposium (IV), p. 1143-1149
(Conference paper)
https://dx.doi.org/10.1109/IVS.2018.8500676