Johannes Fischer

M.Sc. Johannes Fischer

  • Karlsruher Institut für Technologie (KIT)
    Institut für Mess- und Regelungstechnik
    Engler-Bunte-Ring 21
    Gebäude 40.32
    D-76131 Karlsruhe

Forschung

Lehre

Zu vergebende Abschlussarbeiten

Veröffentlichungen

Christoph Burger, Johannes Fischer, Frank Bieder, Ömer Şahin Taş, Christoph Stiller. Interaction-Aware Game-Theoretic Motion Planning for Automated Vehicles using Bi-level Optimization. In IEEE International Intelligent Transportation Systems Conference (ITSC), Macau, China, October 2022. (2nd Place "Best Paper Award"). [ .pdf ]

Arec Jamgochian, Etienne Buehrle, Johannes Fischer, Mykel J. Kochenderfer. SHAIL: Safety-Aware Hierarchical Adversarial Imitation Learning for Autonomous Driving in Urban Environments. arXiv:2204.01922 [cs], 2022.

Danial Kamran, Thiago Simão, Qisong Yang, Canmanie Ponnambalam, Johannes Fischer, Matthijs Spaan, Martin Lauer. A Modern Perspective on Safe Automated Driving for Different Traffic Dynamics using Constrained Reinforcement Learning. In Proc. IEEE Intell. Trans. Syst. Conf., Macau, China, 10 2022.

Johannes Fischer, Etienne Bührle, Danial Kamran, Christoph Stiller. Guiding Belief Space Planning with Learned Models for Interactive Merging. In Proc. IEEE Intell. Trans. Syst. Conf., Macau, China, 10 2022.

Johannes Fischer, Christoph Eyberg, Moritz Werling, Martin Lauer. Sampling-Based Inverse Reinforcement Learning Algorithms with Safety Constraints. In 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Seiten 791--798, September 2021. [ DOI ]

Danial Kamran, Tizian Engelgeh, Marvin Busch, Johannes Fischer, Christoph Stiller. Minimizing Safety Interference for Safe and Comfortable Automated Driving with Distributional Reinforcement Learning. In IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Prague, Czech Republic, September 2021. accepted.

Johannes Fischer, Ömer Sahin Tas. Information Particle Filter Tree: An Online Algorithm for POMDPs with Belief-Based Rewards on Continuous Domains. In Proceedings of the 37th International Conference on Machine Learning (ICML), Vienna, Austria, July 2020. [ .html ]