Lasse Peters


About Me

I am a third-year PhD candidate at the Department of Cognitive Robotics (CoR) at Delft University of Technology working with Prof. Javier Alonso-Mora and Prof. Laura Ferranti. My research interests focus on combining methods from optimal control, game theory, and reinforcement learning to design control strategies for multi-agent systems under uncertainty.

Before coming to Delft, I worked as a full-time research scholar at the Photogrammetry & Robotics Lab at University of Bonn under the supervision of Prof. Cyrill Stachniss. There, I developed methods for solving inverse games in continuous state-action spaces.

I received a M.Sc Mechatronics and a B.Sc. in Mechanical Engineering from TU Hamburg, Germany, in 2020 and 2017, respectively. During that time, I was a member of the university’s RoboCup SPL team and later a visiting student and research scholar at UC Berkeley where I worked with Prof. Claire J. Tomlin and Prof. Zachary N. Sunberg at the Hybrid Systems Laboratory. There, I also wrote my master’s thesis on “Accommodating Intention Uncertainty in General-Sum Games for Human-Robot Interaction”.


For coordinating meetings, this calendar shows times when I will be busy.

PGP: 8A1F6554BF8772E9


  • Dec, 2023. Our work on contingency games has been accepted at IEEE RA-L and will be presented at IROS 2024 in Abu Dhabi.

  • Aug, 2023. New preprint on contingency games: a model for strategic interactions which allows a robot to consider the full distribution of other agents’ intents while anticipating intent certainty in the near future.

  • May, 2023. Our work “Online and Offline Learning of Player Objectives from Partial Observations in Dynamic Games” has been accepted for publication in the International Journal of Robotics Research (IJRR). [website]


cost inference behavior prediction
optimiztion differentiable programming Julia
dynamic games learning differentiable programming
cost inference behavior prediction
behavior prediction dynamic games multi-agent cost inference
humanoid robotics multi-agent RoboCup SPL