2 papers
cs.RO2026
LUCID: Learning Embodiment-Agnostic Intent Models from Unstructured Human Videos for Scalable Dexterous Robot Skill Acquisition
Harsh Gupta, Guanya Shi, Wenzhen Yuan
The most widely-adopted robot learning pipelines today learn skills from robot demonstrations or structured human data, which are expensive to collect and tied to specific embodime…
cs.RO2026
Function-based Parametric Co-Design Optimization of Dexterous Hands
Mohammad Amin Mirzaee, Harsh Gupta, Wenzhen Yuan
Despite advances in dexterous hand manipulation, robotic hand design is still largely decoupled from task-driven evaluation and control, limiting systematic optimization. Existing…