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Fingers as Legs: Learning Self-Supported Locomotion and Manipulation with an Anthropomorphic Hand
The authors train an anthropomorphic robotic hand to crawl, steer, and recover from falls using its fingers for both support and manipulation, via a reinforcement‑learning reward formulation tuned to the hand's asymmetry. Sim‑to‑real experiments show faster locomotion than quadruped‑style rewards and successful untethered tasks without onboard vision.
Hugging Face Daily Papersarxiv.org1 minpaper
