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マニピュレーションarXiv:2310.18425

平面物体群に対する平行グリッパと把持の同時最適化

Parallel-Jaw Gripper and Grasp Co-Optimization for Sets of Planar Objects

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複数の多角形物体を安定に把持できる平行グリッパの形状と把持位置を同時に最適化するフレームワークを提案し、実機実験で検証した。

著者: Rebecca H. Jiang, Neel Doshi, Ravi Gondhalekar, Alberto Rodriguez

分類: cs.RO

原文アブストラクト

We propose a framework for optimizing a planar parallel-jaw gripper for use with multiple objects. While optimizing general-purpose grippers and contact locations for grasps are both well studied, co-optimizing grasps and the gripper geometry to execute them receives less attention. As such, our framework synthesizes grippers optimized to stably grasp sets of polygonal objects. Given a fixed number of contacts and their assignments to object faces and gripper jaws, our framework optimizes contact locations along these faces, gripper pose for each grasp, and gripper shape. Our key insights are to pose shape and contact constraints in frames fixed to the gripper jaws, and to leverage the linearity of constraints in our grasp stability and gripper shape models via an augmented Lagrangian formulation. Together, these enable a tractable nonlinear program implementation. We apply our method to several examples. The first illustrative problem shows the discovery of a geometrically simple solution where possible. In another, space is constrained, forcing multiple objects to be contacted by the same features as each other. Finally a toolset-grasping example shows that our framework applies to complex, real-world objects. We provide a physical experiment of the toolset grasps.

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