Photo of Mattias Tiger

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 study trajectory modeling, motion planning, and runtime monitoring for autonomous robots and decision-support systems, with particular emphasis on uncertainty management, anomaly detection, and safety guarantees during operation. My work spans both fundamental methods and applied research in close collaboration with industry and public-sector partners, including transportation, robotics, and public safety.

​​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

robot dog Spot, drone, small helicopter, operator

WASP at Department of Computer and Information Science (IDA)

WASP, Wallenberg AI autonomous systems and software program, is the largest individual research investment in Sweden in modern times. One of the WASP research environments at LiU is located at the Department of Computer and Information Science.

Coverage Path Planning in Urban Environments with Applications to Autonomous Road Sweeping

 Video 

2022 IEEE International Conferance on Robotics and Automation (ICRA)


Enhancing Lattice-based Motion Planning with Introspective Learning and Reasoning

 Video 

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

 Video 

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

 Video 

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.

Students discussing programming code at a computer screen

AI Academy

AI Academy is an initiative that seeks to challenge talented students from a wide variety of programmes with exciting real-world AI problems.

Publications

2025

Emil Wiman, Mattias Tiger (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) Continue to DOI

2024

Lidia Rocha, Jorge Bidinotto, Fredrik Heintz, Mattias Tiger, Kelen Vivaldini (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) Continue to DOI
Emil Wiman, Ludvig Widén, Mattias Tiger, Fredrik Heintz (2024) Autonomous 3D Exploration in Large-Scale Environments with Dynamic Obstacles 2024 IEEE International Conference on Robotics and Automation (ICRA), p. 2389-2395 (Conference paper) Continue to DOI
Emil Wiman, Ludvig Widén, Mattias Tiger, Fredrik Heintz (2024) Autonomous 3D Exploration in Large-Scale Environments with Dynamic Obstacles

2023

Mattias Tiger, David Bergström, Simon Wijk Stranius, Evelina Holmgren, Daniel de Leng, Fredrik Heintz (2023) On-Demand Multi-Agent Basket Picking for Shopping Stores 2023 IEEE International Conference on Robotics and Automation (ICRA), p. 5793-5799 (Conference paper) Continue to DOI

2022

Mattias Tiger (2022) Safety-Aware Autonomous Systems: Preparing Robots for Life in the Real World
Daniel Engelsons, Mattias Tiger, Fredrik Heintz (2022) 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) Continue to DOI

2021

Mattias Tiger, David Bergström, Andreas Norrstig, Fredrik Heintz (2021) Enhancing Lattice-Based Motion Planning With Introspective Learning and Reasoning IEEE Robotics and Automation Letters, Vol. 6, p. 4385-4392 (Article in journal) Continue to DOI

2020

Fredrik Präntare, Mattias Tiger, David Bergström, Herman Appelgren, Fredrik Heintz (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) Continue to DOI
Mattias Tiger, Fredrik Heintz (2020) 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)
Mattias Tiger, Fredrik Heintz (2020) 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) Continue to DOI

2019

David Bergström, Mattias Tiger, Fredrik Heintz (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)
Magnus Selin, Mattias Tiger, Daniel Duberg, Fredrik Heintz, Patric Jensfelt (2019) Efficient Autonomous Exploration Planning of Large Scale 3D-Environments IEEE Robotics and Automation Letters, Vol. 4, p. 1699-1706 (Article in journal) Continue to DOI

2018

Olov Andersson, Oskar Ljungqvist, Mattias Tiger, Daniel Axehill, Fredrik Heintz (2018) Receding-Horizon Lattice-based Motion Planning with Dynamic Obstacle Avoidance 2018 IEEE Conference on Decision and Control (CDC), p. 4467-4474 (Conference paper) Continue to DOI
Mattias Tiger, Fredrik Heintz (2018) Gaussian Process Based Motion Pattern Recognition with Sequential Local Models 2018 IEEE Intelligent Vehicles Symposium (IV), p. 1143-1149 (Conference paper) Continue to DOI

Research News

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