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マニピュレーションarXiv:2411.07833

触覚センシングを用いたロバスト適応安全ロボット把持

Robust Adaptive Safe Robotic Grasping with Tactile Sensing

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触覚センサから接触点・力・トルクを推定し、制御バリア関数に基づく安全フィルタで把持力を制御することで、壊れやすい物体でも安全に把持できる枠組みを提案した。

著者: Yitaek Kim, Jeeseop Kim, Albert H. Li, Aaron D. Ames, Christoffer Sloth

分類: cs.RO, cs.SY, eess.SY

原文アブストラクト

Robotic grasping requires safe force interaction to prevent a grasped object from being damaged or slipping out of the hand. In this vein, this paper proposes an integrated framework for grasping with formal safety guarantees based on Control Barrier Functions. We first design contact force and force closure constraints, which are enforced by a safety filter to accomplish safe grasping with finger force control. For sensory feedback, we develop a technique to estimate contact point, force, and torque from tactile sensors at each finger. We verify the framework with various safety filters in a numerical simulation under a two-finger grasping scenario. We then experimentally validate the framework by grasping multiple objects, including fragile lab glassware, in a real robotic setup, showing that safe grasping can be successfully achieved in the real world. We evaluate the performance of each safety filter in the context of safety violation and conservatism, and find that disturbance observer-based control barrier functions provide superior performance for safety guarantees with minimum conservatism.

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