6 papers · 1 filter
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…
A Careful Examination of Large Behavior Models for Multitask Dexterous Manipulation
TRI LBM Team, Jose Barreiros, Andrew Beaulieu +79
Robot manipulation has seen tremendous progress in recent years, with imitation learning policies enabling successful performance of dexterous and hard-to-model tasks. Concurrently…
Adaptive Compliance Policy: Learning Approximate Compliance for Diffusion Guided Control
Yifan Hou, Zeyi Liu, Cheng Chi +5
Compliance plays a crucial role in manipulation, as it balances between the concurrent control of position and force under uncertainties. Yet compliance is often overlooked by toda…
RLDG: Robotic Generalist Policy Distillation via Reinforcement Learning
Charles Xu, Qiyang Li, Jianlan Luo +1
Recent advances in robotic foundation models have enabled the development of generalist policies that can adapt to diverse tasks. While these models show impressive flexibility, th…
ManiWAV: Learning Robot Manipulation from In-the-Wild Audio-Visual Data
Zeyi Liu, Cheng Chi, Eric Cousineau +3
Audio signals provide rich information for the robot interaction and object properties through contact. This information can surprisingly ease the learning of contact-rich robot ma…
Vegetable Peeling: A Case Study in Constrained Dexterous Manipulation
Tao Chen, Eric Cousineau, Naveen Kuppuswamy +1
Recent studies have made significant progress in addressing dexterous manipulation problems, particularly in in-hand object reorientation. However, there are few existing works tha…