AnyDexRT：基于少量人类引导的免校准灵巧手重定向
AnyDexRT: Calibration-Free Dexterous Hand Retargeting with Few-Shot Human Guidance
- Shanghai Jiao Tong University（上海交通大学）
- Shanghai Innovation Institute（上海创新研究院）
机构由 AI 辅助整理，请以论文原文为准。
AI总结：
研究提出免校准的AnyDexRT方法用于灵巧手遥操作重定向，结合自监督指尖对应学习与少量人类引导，在任务相关区域锚定映射并优化捏合姿势，实验表明该方法提升重定向质量、减少手动调整，控制更直观高效。
AI中文摘要：
遥操作是控制灵巧机器人手和收集模仿学习演示的关键接口。其有效性很大程度上取决于运动重定向，即将操作员手部动作映射到可行且直观的机器人手部动作。现有方法通常需要手工目标、精确校准或人与机器人手部空间之间的全局形状匹配，对手部特定调整敏感且跨不同灵巧手可靠性较低。我们提出AnyDexRT，一种用于跨类人灵巧手进行直观灵巧遥操作的免校准重定向方法。AnyDexRT将自监督指尖对应学习与少量人类引导相结合，以在任务相关区域锚定映射，并使用接触分类器进一步优化捏合相关姿势。在不同灵巧手和现实世界遥操作任务上的实验表明，AnyDexRT提高了重定向质量，减少了手动调整，并且比先前的重定向方法提供了更直观和高效的控制。
英文摘要：
Teleoperation is a key interface for controlling dexterous robotic hands and collecting demonstrations for imitation learning. Its effectiveness largely depends on kinematic retargeting, which maps operator hand motions to feasible and intuitive robot hand motions. Existing methods often require hand-crafted objectives, precise calibration, or global shape matching between human and robot hand spaces, making them sensitive to hand-specific tuning and less reliable across different dexterous hands. We propose AnyDexRT, a calibration-free retargeting method for intuitive dexterous teleoperation across human-like dexterous hands. AnyDexRT combines self-supervised fingertip correspondence learning with few-shot human guidance to anchor the mapping in task-relevant regions, and further refines pinch-related poses using a contact classifier. Experiments on diverse dexterous hands and real-world teleoperation tasks show that AnyDexRT improves retargeting quality, reduces manual tuning, and provides more intuitive and efficient control than prior retargeting methods. Project website: https://chenxi-wang.github.io/projects/anydexrt
