| UMBRELLA: Uncertainty-Aware Model-Based Offline Reinforcement Learning Leveraging Planning C Diehl, T Sievernich, M Krüger, F Hoffmann, T Bertram Best Paper Award, Neural Information Processing Systems 34 - Machine …, 2021 | 11 | 2021 |
| Radar-based Dynamic Occupancy Grid Mapping and Object Detection C Diehl, E Feicho, A Schwambach, T Dammeier, E Mares, T Bertram 2020 IEEE 23rd International Conference on Intelligent Transportation …, 2020 | 11 | 2020 |
| Uncertainty-Aware Model-Based Offline Reinforcement Learning for Automated Driving C Diehl, TS Sievernich, M Krüger, F Hoffmann, T Bertram IEEE Robotics and Automation Letters, 2023 | 1 | 2023 |
| Time-Optimal Nonlinear Model Predictive Control for Radar-based Automated Parking C Diehl, A Makarow, C Rösmann, B Torsten IFAC Symposium on Intelligent Autonomous Vehicles, IAV 2022, 2022 | 1 | 2022 |
| Navigation with Uncertain Map Data for Automated Vehicles C Diehl, N Stannartz, T Bertram Automated Driving 2021, 143-157, 2021 | 1 | 2021 |
| Conditional Behavior Prediction for Automated Driving on Highways C Diehl, T Osterburg, N Murzyn, G Schneider, F Hoffmann, T Bertram Proc. 32. Workshop Computational Intelligence 1, 125, 2022 | | 2022 |
| Differentiable Constrained Imitation Learning for Robot Motion Planning and Control C Diehl, J Adamek, M Krüger, F Hoffmann, T Bertram arXiv preprint arXiv:2210.11796, 2022 | | 2022 |
| Recognition Beyond Perception: Environmental Model Completion by Reasoning for Occluded Vehicles M Krueger, P Palmer, C Diehl, T Osterburg, T Bertram IEEE Robotics and Automation Letters, 2022 | | 2022 |
| VectorRL: Interpretable Graph-based Reinforcement Learning for Automated Driving C Diehl, T Waldeyer, F Hoffmann, T Bertram Proc. 31. Workshop Computational Intelligence, 2021 | | 2021 |
Frank HoffmannTU DortmundVerified email at tu-dortmund.de
