5 papers
DexAgent: An Agentic Human2Sim2Robot Framework for Dexterous Manipulation with Self-Evolving Tool Library
Youhui Wang, Yunzhu Li, Li Fei-Fei +2
Human videos offer a scalable source of demonstrations for dexterous robot manipulation. However, existing human-to-simulation-to-robot (Human2Sim2Robot) pipelines rely on predefin…
One Demonstration, Many Objects: Generalizing Manipulation via Local Contact Geometry
Satvik Sharma, Samrat Sahoo, Huang Huang +4
Dexterous manipulation with multi-fingered robot hands promises human-level dexterity, but collecting large-scale dexterous robot hand data remains difficult. Learning from human d…
GET-USE: Learning Generalized Tool Usage for Bimanual Mobile Manipulation via Simulated Embodiment Extensions
Bohan Wu, Paul de La Sayette, Li Fei-Fei +1
The ability to use random objects as tools in a generalizable manner is a missing piece in robots' intelligence today to boost their versatility and problem-solving capabilities. S…
MoMaGen: Generating Demonstrations under Soft and Hard Constraints for Multi-Step Bimanual Mobile Manipulation
Chengshu Li, Mengdi Xu, Arpit Bahety +11
Imitation learning from large-scale, diverse human demonstrations has been shown to be effective for training robots, but collecting such data is costly and time-consuming. This ch…
Why Automate This? Exploring Correlations Between Desire for Robotic Automation, Invested Time and Well-Being
Ruchira Ray, Leona Pang, Sanjana Srivastava +3
Understanding the motivations underlying the human inclination to automate tasks is vital for developing robots that fit seamlessly into daily life. Accordingly, we ask: are indivi…