外观
论文arXiv 2609.187631 个月前
用于全身人形机器人遥操作的门控残差身体-手部协调
原文链接：Gated Residual Body-Hand Coordination for Whole-Body Humanoid Teleoperation（arXiv 2609.18763 · 发布日期：2026-09-16）
Gated Residual Body-Hand Coordination for Whole-Body Humanoid Teleoperation
针对人形遥操作中身体与手部命令失配，提出门控残差协调，在仿真GRAB与AMASS动作上验证。
核心要点
- 问题/动机：独立的运动跟踪与灵巧手重定向难以保持腕部和指尖几何关系。
- 方法：冻结原模块，对输出施加有界残差修正，并用动作门和奖励门分配协调目标。
- 为Agile One建立标称身体控制器，结合多姿态形态校准与分阶段动作数据整理。
- 实验：仿真中较直接组合降低几何误差39.2-56.3%，AMASS成功率基本保持。
验证范围与局限：验证仅在仿真中进行，覆盖held-out GRAB动作与AMASS全身跟踪。
英文摘要 (Abstract)
Whole-body humanoid teleoperation commonly combines a motion-tracking policy with a separate dexterous-hand retargeter. However, independently generated commands do not explicitly preserve body-hand geometric relations, leading to mismatches in relative wrist poses and fingertip positions during bimanual interaction. We present a gated residual coordination framework that keeps both modules frozen and applies bounded corrections to their outputs. A motion-conditioned action gate allocates correction authority across joint groups, while reference-geometry-dependent reward gates emphasize relevant interaction objectives during training. To establish the nominal body controller on Agile One, we introduce multi-pose morphology calibration that jointly estimates triaxial scales and effector-local offsets, together with staged motion dataset curation for training a SONIC-based tracker. The residual policy uses human motion references, initial commands, and robot proprioception without explicit object or contact observations. In simulation, it reduces wrist and fingertip geometry errors by 39.2-56.3% over direct composition on held-out GRAB motions, while preserving whole-body tracking on AMASS, with success rates of 89.03% without residual coordination and 89.29% with it. Ablations characterize the contributions of reward gating, adaptive correction authority, and separate body and hand correction heads.
作者：Ruiming Wu, Shuang Li, Liding Zhang, Alois Knoll, Zhaopeng Chen
来源
本页事实对应的公开页面，以原文为准。