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マニピュレーションarXiv:2502.07472

大範囲で高精度な物体移動を実現するロボットハンド内マニピュレーション:RGMC優勝ソリューション

Robotic In-Hand Manipulation for Large-Range Precise Object Movement: The RGMC Champion Solution

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指先のみで把持中の物体を安定に保ちながら高精度かつ広範囲に動かすため、物体形状や事前学習を必要としない運動学的軌道最適化手法を提案し、ICRA 2024のRGMCハンド内操作部門で優勝した。

著者: Mingrui Yu, Yongpeng Jiang, Chen Chen, Yongyi Jia, Xiang Li

分類: cs.RO

原文アブストラクト

In-hand manipulation using multiple dexterous fingers is a critical robotic skill that can reduce the reliance on large arm motions, thereby saving space and energy. This letter focuses on in-grasp object movement, which refers to manipulating an object to a desired pose through only finger motions within a stable grasp. The key challenge lies in simultaneously achieving high precision and large-range movements while maintaining a constant stable grasp. To address this problem, we propose a simple and practical approach based on kinematic trajectory optimization with no need for pretraining or object geometries, which can be easily applied to novel objects in real-world scenarios. Adopting this approach, we won the championship for the in-hand manipulation track at the 9th Robotic Grasping and Manipulation Competition (RGMC) held at ICRA 2024. Implementation details, discussion, and further quantitative experimental results are presented in this letter, which aims to comprehensively evaluate our approach and share our key takeaways from the competition. Supplementary materials including video and code are available at https://rgmc-xl-team.github.io/ingrasp_manipulation .

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