シミュレーション駆動の進化的動作パラメータ化による柔軟円錐ロボットハンドを用いた接触リッチな粒状物すくい上げ
Simulation-Driven Evolutionary Motion Parameterization for Contact-Rich Granular Scooping with a Soft Conical Robotic Hand
柔軟な円錐形ロボットハンドの変形を物理シミュレーションでモデル化し、進化的戦略によりすくい上げ軌道を自動最適化する手法を提案。シミュレーションと実機実験で汎化性能を検証した。
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著者: Yongliang Wang, Cristian C. Beltran-Hernandez, Tomoya Takahashi, Masashi Hamaya
分類: cs.RO
原文アブストラクト
Tool-based scooping is vital in robot-assisted tasks, enabling interaction with objects of varying sizes, shapes, and material states. Recent studies have shown that flexible, reconfigurable soft robotic end-effectors can adapt their shape to maintain consistent contact with container surfaces during scooping, improving efficiency compared to rigid tools. These soft tools can adjust to varying container sizes and materials without requiring complex sensing or control. However, the inherent compliance and complex deformation behavior of soft robotics introduce significant control complexity that limits practical applications. To address this challenge, this paper presents the development of a physics-based simulation model of a deformable soft conical robotic hand that captures its passive reconfiguration dynamics and enables systematic trajectory optimization for scooping tasks. We propose a novel physics-based simulation approach that accurately models the soft tool's morphing behavior from flat sheets to adaptive conical structures, combined with an evolutionary strategy framework that automatically optimizes scooping trajectories without manual parameter tuning. We validate the optimized trajectories through both simulation and real-robot experiments. The results demonstrate strong generalization and successfully address a range of challenging tasks previously beyond the reach of existing approaches. Videos of our experiments are available online: https://sites.google.com/view/scoopsh
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