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Energy-based Potential Games for Joint Motion Forecasting and Control
Christopher Diehl, Tobias Klosek, Martin Krüger, Nils Murzyn, Timo Osterburg, Torsten Bertram
Energy-based Potential Games for Joint Motion Forecasting and Control
Differentiable Constrained Imitation Learning for Robot Motion Planning and Control
Christopher Diehl, Janis Adamek, Martin Krüger, Frank Hoffmann, Torsten Bertram
Differentiable Constrained Imitation Learning for Robot Motion Planning and Control
On a Connection between Differential Games, Optimal Control, and Energy-based Models for Multi-Agent Interactions
Christopher Diehl, Tobias Klosek, Martin Krüger, Nils Murzyn, Torsten Bertram
On a Connection between Differential Games, Optimal Control, and Energy-based Models for Multi-Agent Interactions
Social Behavior Prediction for Automated Vehicles Using Contrastive Learning
Timo Osterburg, Christopher Diehl, Torsten Bertram
Conditional Behavior Prediction for Automated Driving on Highways
Christopher Diehl, Timo Osterburg, Nils Murzyn, Georg Schneider, Frank Hoffmann, Torsten Bertram
Conditional Behavior Prediction for Automated Driving on Highways
Beyond Perception: Environmental Model Completion by Reasoning for Occluded Vehicles
Martin Krüger, Patrick Palmer, Christopher Diehl, Timo Osterburg, Torsten Bertram
Time‑Optimal Nonlinear Model Predictive Control for Radar‑based Automated Parking
Christopher Diehl, Artemi Makarow, Christoph Rösmann, Torsten Bertram
Time‑Optimal Nonlinear Model Predictive Control for Radar‑based Automated Parking
UMBRELLA: Uncertainty-Aware Model-Based Offline Reinforcement Learning Leveraging Planning
Christopher Diehl, Timo Sievernich, Martin Krüger, Frank Hoffmann, Torsten Bertram
UMBRELLA: Uncertainty-Aware Model-Based Offline Reinforcement Learning Leveraging Planning
VectorRL: Interpretable Graph‑based Reinforcement Learning for Automated Driving
Christopher Diehl, Tamino Waldeyer, Frank Hoffmann, Torsten Bertram
VectorRL: Interpretable Graph‑based Reinforcement Learning for Automated Driving