Robust Anthropomorphic Robotic Manipulation through Biomimetic Distributed Compliance
arxiv(2024)
摘要
The impressive capabilities of humans to robustly perform manipulation relies
on compliant interactions, enabled through the structure and materials
spatially distributed in our hands. We propose by mimicking this distributed
compliance in an anthropomorphic robotic hand, the open-loop manipulation
robustness increases and observe the emergence of human-like behaviours. To
achieve this, we introduce the ADAPT Hand equipped with tunable compliance
throughout the skin, fingers, and the wrist. Through extensive automated
pick-and-place tests, we show the grasping robustness closely mirrors an
estimated geometric theoretical limit, while `stress-testing' the robot hand to
perform 800+ grasps. Finally, 24 items with largely varying geometries are
grasped in a constrained environment with a success rate of 93%. We
demonstrate the hand-object self-organization behavior underlines this extreme
robustness, where the hand automatically exhibits different grasp types
depending on object geometries. Furthermore, the robot grasp type mimics a
natural human grasp with a direct similarity of 68%.
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