CoCarry: 接触・支持構造を考慮した二体ヒューマノイド協調運搬のリターゲティング
CoCarry: Contact-Support-Structured Retargeting for Dual-Humanoid Cooperative Carrying
220本の二人協調運搬モーションデータセットCoCarryを構築し、同一物体軌道の周りで両ヒューマノイドを協調的に調整する接触・支持構造リターゲティング手法を提案した。
詳しい要約
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2. 先行研究と比べてどこがすごい?
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著者: Ziyu Lin, Shihang Du, Tianhang Wang, Xiaodong Liu, Runze Zhang, Zongyou Yu, Haodong Zhang, Alois Knoll, Guang Chen
分類: cs.RO
原文アブストラクト
Recent advances in large-scale human motion data, motion retargeting, and motion imitation have enabled increasingly capable whole-body control for individual humanoids. Cooperative carrying is more challenging because successful coordination requires not only plausible individual motions, but also consistent cross-agent and agent-object relations, including shared grasp, relative configuration, and whole-body support. We introduce CoCarry, a cooperative-carrying dataset containing 220 synchronized two-person sequences across 21 task schemes, five shared-object geometries, four terrain types, and approximately 61 minutes of motion. We further propose Contact-Support-Structured Retargeting, which starts from nominal individual motions and jointly refines both humanoids around the same prescribed object trajectory. Cooperation-aware object-local hand anchors preserve compatible four-hand grasp relations, while complementary upper object-interaction and lower support structures retain object-relative geometry and coordinated support. Across all 220 CoCarry sequences retargeted to two A3 humanoids, our method achieves 0.9995 contact preservation, reduces penetration duration by 67.0% and 71.0% relative to GMR and OmniRetarget, respectively, and maintains a 100% retargeting success rate. On CORE4D with Unitree G1 humanoids, it achieves 0.9906 contact preservation with zero measured sliding. We further validate the generated references through physics simulation and multiple real-world cooperative carrying experiments on two physical A3 humanoids, demonstrating their usability for downstream dual-humanoid control.