13 citations · 23 across the 5 of their papers we have counts for
5 papers
From a Single Demonstration to a General Policy for Contact-Rich Manipulation
Xing Li, Oliver Brock
We present a Learning from Demonstration (LfD) framework that achieves one-shot generalization in multi-stage, contact-rich manipulation tasks. Central to our approach is the utili…
AsyncShield: A Plug-and-Play Edge Adapter for Asynchronous Cloud-based VLA Navigation
Kai Yang, Zedong Chu, Yingnan Guo +6
While Vision-Language-Action (VLA) models have been demonstrated possessing strong zero-shot generalization for robot control, their massive parameter sizes typically necessitate c…
Augmentation for Learning From Demonstration with Environmental Constraints
Xing Li, Manuel Baum, Oliver Brock
We introduce a Learning from Demonstration (LfD) approach for contact-rich manipulation tasks with articulated mechanisms. The extracted policy from a single human demonstration ge…
Planning on the fast lane: Learning to interact using attention mechanisms in path integral inverse reinforcement learning
Sascha Rosbach, Xing Li, Simon Großjohann +2
General-purpose trajectory planning algorithms for automated driving utilize complex reward functions to perform a combined optimization of strategic, behavioral, and kinematic fea…
Driving Style Encoder: Situational Reward Adaptation for General-Purpose Planning in Automated Driving
Sascha Rosbach, Vinit James, Simon Großjohann +3
General-purpose planning algorithms for automated driving combine mission, behavior, and local motion planning. Such planning algorithms map features of the environment and driving…