【スポンジ拭き】人間の"当たり前"がロボットに不可能な理由 скачать в хорошем качестве

【スポンジ拭き】人間の"当たり前"がロボットに不可能な理由

論文情報 ・url: http://arxiv.org/html/2603.03137v1 ・title: RL-Based Coverage Path Planning for Deformable Objects on 3D Surfaces ・abstract: Currently, manipulation tasks for deformable objects often focus on activities like folding clothes, handling ropes, and manipulating bags. However, research on contact-rich tasks involving deformable objects remains relatively underdeveloped. When humans use cloth or sponges to wipe surfaces, they rely on both vision and tactile feedback. Yet, current algorithms still face challenges with issues like occlusion, while research on tactile perception for manipulation is still evolving. Tasks such as covering surfaces with deformable objects demand not only perception but also precise robotic manipulation. To address this, we propose a method that leverages efficient and accessible simulators for task execution. Specifically, we train a reinforcement learning agent in a simulator to manipulate deformable objects for surface wiping tasks. We simplify the state representation of object surfaces using harmonic UV mapping, process contact feedback from the simulator on 2D feature maps, and use scaled grouped convolutions (SGCNN) to extract features efficiently. The agent then outputs actions in a reduced-dimensional action space to generate coverage paths. Experiments demonstrate that our method outperforms previous approaches in key metrics, including total path length and coverage area. We deploy these paths on a Kinova Gen3 manipulator to perform wiping experiments on the back of a torso model, validating the feasibility of our approach. ========== スポンジで表面を拭く――人間なら無意識にできるこの動作が、ロボットにとっては超難題。中国科学技術大学とシャオミが開発した強化学習AIは、3D曲面を27%効率化して拭き上げることに成功。介護、清掃、製造業の未来を変える「変形物体操作技術」の最前線を解説します。あなたの仕事も、この技術で変わるかもしれません。