3 citations · 7 across the 6 of their papers we have counts for
9 papers · 1 filter
Lightning Grasp: High Performance Procedural Grasp Synthesis with Contact Fields
Zhao-Heng Yin, Pieter Abbeel
Despite years of research, real-time diverse grasp synthesis for dexterous hands remains an unsolved core challenge in robotics and computer graphics. We present Lightning Grasp, a…
Object-centric 3D Motion Field for Robot Learning from Human Videos
Zhao-Heng Yin, Sherry Yang, Pieter Abbeel
Learning robot control policies from human videos is a promising direction for scaling up robot learning. However, how to extract action knowledge (or action representations) from…
RoboCopilot: Human-in-the-loop Interactive Imitation Learning for Robot Manipulation
Philipp Wu, Yide Shentu, Qiayuan Liao +5
Learning from human demonstration is an effective approach for learning complex manipulation skills. However, existing approaches heavily focus on learning from passive human demon…
DexterityGen: Foundation Controller for Unprecedented Dexterity
Zhao-Heng Yin, Changhao Wang, Luis Pineda +11
Teaching robots dexterous manipulation skills, such as tool use, presents a significant challenge. Current approaches can be broadly categorized into two strategies: human teleoper…
Hand-Object Interaction Pretraining from Videos
Himanshu Gaurav Singh, Antonio Loquercio, Carmelo Sferrazza +4
We present an approach to learn general robot manipulation priors from 3D hand-object interaction trajectories. We build a framework to use in-the-wild videos to generate sensorimo…
From LLMs to Actions: Latent Codes as Bridges in Hierarchical Robot Control
Yide Shentu, Philipp Wu, Aravind Rajeswaran +1
Hierarchical control for robotics has long been plagued by the need to have a well defined interface layer to communicate between high-level task planners and low-level policies. W…