1 citations · 2 across the 5 of their papers we have counts for
6 papers · 1 filter
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…
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…
Skill Generalization with Verbs
Rachel Ma, Lyndon Lam, Benjamin A. Spiegel +6
It is imperative that robots can understand natural language commands issued by humans. Such commands typically contain verbs that signify what action should be performed on a give…
RMPs for Safe Impedance Control in Contact-Rich Manipulation
Seiji Shaw, Ben Abbatematteo, George Konidaris
Variable impedance control in operation-space is a promising approach to learning contact-rich manipulation behaviors. One of the main challenges with this approach is producing a…
Bootstrapping Motor Skill Learning with Motion Planning
Ben Abbatematteo, Eric Rosen, Stefanie Tellex +1
Learning a robot motor skill from scratch is impractically slow; so much so that in practice, learning must be bootstrapped using a good skill policy obtained from human demonstrat…