3 citations · 4 across the 3 of their papers we have counts for
5 papers
Doing Right by Not Doing Wrong in Human-Robot Collaboration
Laura Londoño, Adrian Röfer, Tim Welschehold +1
As robotic systems become more and more capable of assisting humans in their everyday lives, we must consider the opportunities for these artificial agents to make their human coll…
Courteous Behavior of Automated Vehicles at Unsignalized Intersections via Reinforcement Learning
Shengchao Yan, Tim Welschehold, Daniel Büscher +1
The transition from today's mostly human-driven traffic to a purely automated one will be a gradual evolution, with the effect that we will likely experience mixed traffic in the n…
Learning Kinematic Feasibility for Mobile Manipulation through Deep Reinforcement Learning
Daniel Honerkamp, Tim Welschehold, Abhinav Valada
Mobile manipulation tasks remain one of the critical challenges for the widespread adoption of autonomous robots in both service and industrial scenarios. While planning approaches…
Combined Task and Action Learning from Human Demonstrations for Mobile Manipulation Applications
Tim Welschehold, Nichola Abdo, Christian Dornhege +1
Learning from demonstrations is a promising paradigm for transferring knowledge to robots. However, learning mobile manipulation tasks directly from a human teacher is a complex pr…
3D Human Pose Estimation in RGBD Images for Robotic Task Learning
Christian Zimmermann, Tim Welschehold, Christian Dornhege +2
We propose an approach to estimate 3D human pose in real world units from a single RGBD image and show that it exceeds performance of monocular 3D pose estimation approaches from c…