3 papers
cs.RO2026
One Demo is Worth a Thousand Trajectories: Action-View Augmentation for Visuomotor Policies
Chuer Pan, Litian Liang, Dominik Bauer +4
Visuomotor policies for manipulation have demonstrated remarkable potential in modeling complex robotic behaviors, yet minor alterations in the robot's initial configuration and un…
cs.RO2026
Universal Manipulation Exoskeleton: Learning Compliant Whole-body Policies with Real-time Torque Feedback
Litian Liang, Jingxi Xu, Xinda Qi +7
For robots to work safely in household environments, they need to be compliant and react to torque and force feedback during contact. However, the majority of existing data collect…
cs.CV2024
When Should We Prefer State-to-Visual DAgger Over Visual Reinforcement Learning?
Tongzhou Mu, Zhaoyang Li, StanisÅaw Wiktor Strzelecki +4
Learning policies from high-dimensional visual inputs, such as pixels and point clouds, is crucial in various applications. Visual reinforcement learning is a promising approach th…