5 papers
Semantic Haptic Feedback Enhances Dexterous Robotic Teleoperation
Bingjian Huang, Sahar Aseeri, Jonas Schmidtler +9
In robot teleoperation, haptic feedback can be used to help human operators accomplish dexterous manipulation tasks. However, existing haptic feedback methods try to replicate high…
Contact-Grounded Policy: Dexterous Visuotactile Policy with Generative Contact Grounding
Zhengtong Xu, Yeping Wang, Ben Abbatematteo +4
Contact-rich dexterous manipulation with multi-finger hands remains an open challenge in robotics because task success depends on multi-point contacts that continuously evolve and…
Tube Diffusion Policy: Reactive Visual-Tactile Policy Learning for Contact-rich Manipulation
Teng Xue, Alberto Rigo, Bingjian Huang +4
Contact-rich manipulation is central to many everyday human activities, requiring continuous adaptation to contact uncertainty and external disturbances through multi-modal percept…
Functional Force-Aware Retargeting from Virtual Human Demos to Soft Robot Policies
Uksang Yoo, Mengjia Zhu, Evan Pezent +8
We introduce SoftAct, a framework for teaching soft robot hands to perform human-like manipulation skills by explicitly reasoning about contact forces. Leveraging immersive virtual…
Stiffness Copilot: An Impedance Policy for Contact-Rich Teleoperation
Yeping Wang, Zhengtong Xu, Pornthep Preechayasomboon +4
In teleoperation of contact-rich manipulation tasks, selecting robot impedance is critical but difficult. The robot must be compliant to avoid damaging the environment, but stiff t…