42 citations · 82 across the 8 of their papers we have counts for
8 papers
On a Connection between Differential Games, Optimal Control, and Energy-based Models for Multi-Agent Interactions
Christopher Diehl, Tobias Klosek, Martin Krüger +2
Game theory offers an interpretable mathematical framework for modeling multi-agent interactions. However, its applicability in real-world robotics applications is hindered by seve…
Differentiable Constrained Imitation Learning for Robot Motion Planning and Control
Christopher Diehl, Janis Adamek, Martin Krüger +2
Motion planning and control are crucial components of robotics applications like automated driving. Here, spatio-temporal hard constraints like system dynamics and safety boundarie…
UMBRELLA: Uncertainty-Aware Model-Based Offline Reinforcement Learning Leveraging Planning
Christopher Diehl, Timo Sievernich, Martin Krüger +2
Offline reinforcement learning (RL) provides a framework for learning decision-making from offline data and therefore constitutes a promising approach for real-world applications a…
Suboptimal nonlinear model predictive control with input move-blocking
Artemi Makarow, Christoph Rösmann, Torsten Bertram
This paper deals with the integration of input move-blocking into the framework of suboptimal model predictive control. The blocked input parameterization is explicitly considered…
Radar-based Dynamic Occupancy Grid Mapping and Object Detection
Christopher Diehl, Eduard Feicho, Alexander Schwambach +3
Environment modeling utilizing sensor data fusion and object tracking is crucial for safe automated driving. In recent years, the classical occupancy grid map approach, which assum…
Online Motion Planning based on Nonlinear Model Predictive Control with Non-Euclidean Rotation Groups
Christoph Rösmann, Artemi Makarow, Torsten Bertram
This paper proposes a novel online motion planning approach to robot navigation based on nonlinear model predictive control. Common approaches rely on pure Euclidean optimization p…
Time-optimal control with direct collocation and variable discretization
Christoph Rösmann, Artemi Makarow, Torsten Bertram
This paper deals with time-optimal control of nonlinear continuous-time systems based on direct collocation. The underlying discretization grid is variable in time, as the time int…
Stabilizing Quasi-Time-Optimal Nonlinear Model Predictive Control with Variable Discretization
Christoph Rösmann, Artemi Makarow, Torsten Bertram
This paper deals with the development and analysis of novel time-optimal point-to-point model predictive control concepts for nonlinear systems. Recent approaches in the literature…