2 citations · 3 across the 5 of their papers we have counts for
5 papers
Energy-based Potential Games for Joint Motion Forecasting and Control
Christopher Diehl, Tobias Klosek, Martin Krüger +3
This work uses game theory as a mathematical framework to address interaction modeling in multi-agent motion forecasting and control. Despite its interpretability, applying game th…
Ego-Motion Estimation and Dynamic Motion Separation from 3D Point Clouds for Accumulating Data and Improving 3D Object Detection
Patrick Palmer, Martin Krueger, Richard Altendorfer +1
New 3+1D high-resolution radar sensors are gaining importance for 3D object detection in the automotive domain due to their relative affordability and improved detection compared t…
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…