単一視点観測による大型物体の実世界協調両手巧緻把持
Real-World Cooperative Bimanual Dexterous Grasp of Large Objects from Single-View Observations
大型物体の両手による協調把持を実世界で実現するため、多モーダルデータセットと拡散モデルを用いた把持生成、および動作計画とオンライン補正を統合したフレームワークを提案した。
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著者: Ziming Li, Mingxuan Wu, Jiaqi Zhang, Hongfei Li, Yan Gan, Deqiang Ouyang, Ning Wang
分類: cs.RO
原文アブストラクト
Bimanual dexterous grasping of large objects is a critical challenge in robotic manipulation. However, most existing studies focus on sequential manipulation rather than cooperative grasping, and methods addressing such bimanual tasks have largely been limited to simulation. These limitations stem from the difficulty of acquiring full 3D object models and generating physically plausible grasping actions. To fill this gap, we propose a real-world bimanual grasping framework that includes: a multimodal dataset capturing joint angles, visual observations and force signals; a Denoising Diffusion Probabilistic Model (DDPM)-based module that generates joint-level grasp configurations from segmented point clouds; and an execution strategy that integrates motion planning with online grasp refinement to ensure physical stability and feasibility. Our approach enables the synthesis of executable bimanual grasps from single-view inputs, reducing dependence on complete 3D object models and ensuring stable real-world performance. Experiments on a dual-arm robot demonstrate high success rates across unseen objects with varying geometries and poses, and ablation studies confirm the contributions of key components of our system.