用人体动作重定向实现20自由度机械手灵巧远程操控
Dexterous Teleoperation of 20-DoF ByteDexter Hand via Human Motion Retargeting
- 通过优化算法将人体动作精准映射到20自由度机械手上
- 实测可在9个物品的杂乱梳妆台任务中完成整理工序
- 适合需要高灵巧度远程操作的研究与工业场景
实现人类级灵巧性仍是机器人领域的核心挑战，需在机电设计与高自由度机器人手控制间协同突破。尽管模仿学习在传递人类灵巧性方面展现潜力，但其性能高度依赖示范数据质量。本文提出一种手-臂遥操作系统：(1) 采用20自由度串联驱动仿人机械手，实现生物仿生灵巧性；(2) 基于优化的动作重定向方法，实时高保真还原复杂人体手部动作，并实现无缝的手-臂协调。通过大量实验验证，包括灵巧的物体内部操控任务及一个包含九种随机物品的长期任务——整理杂乱梳妆台。结果表明该系统具备直观的遥操作界面、实时控制能力，并能生成高质量示范数据。
原文摘要 · Abstract (English)
Replicating human--level dexterity remains a fundamental robotics challenge, requiring integrated solutions from mechatronic design to the control of high degree--of--freedom (DoF) robotic hands. While imitation learning shows promise in transferring human dexterity to robots, the efficacy of trained policies relies on the quality of human demonstration data. We bridge this gap with a hand--arm teleoperation system featuring: (1) a 20--DoF linkage--driven anthropomorphic robotic hand for biomimetic dexterity, and (2) an optimization--based motion retargeting for real--time, high--fidelity reproduction of intricate human hand motions and seamless hand--arm coordination. We validate the system via extensive empirical evaluations, including dexterous in-hand manipulation tasks and a long--horizon task requiring the organization of a cluttered makeup table randomly populated with nine objects. Experimental results demonstrate its intuitive teleoperation interface with real--time control and the ability to generate high--quality demonstration data. Please refer to the accompanying video for further details.
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