用可穿戴外骨骼系统实现高效精准的手部技能数据采集。
Exo-ViHa: A Cross-Platform Exoskeleton System with Visual and Haptic Feedback for Efficient Dexterous Skill Learning
- 3D打印外骨骼+视觉触觉反馈，第一视角采集动作数据。
- 多模态数据同步采集，提升演示与机器人执行的一致性。
- 兼容多种机械臂和灵巧手，适合工业级技能学习场景。
模仿学习已成为机器人灵巧操作技能学习的重要范式。然而，传统灵巧操作的数据采集系统在效率、一致性和准确性之间难以平衡。为此，我们提出 Exo-ViHa，一种创新的3D打印外骨骼系统，支持用户以第一人称视角进行数据采集，并提供实时触觉反馈。该系统结合3D打印模块化结构、SLAM相机、动作捕捉手套和腕部摄像头，可在末端安装多种灵巧手，同步采集末端执行器姿态、手部运动及视觉数据。通过第一人称视角与直接交互，外骨骼提升了任务真实感与触觉反馈，显著增强示范与实际机器人部署之间的一致性。此外，系统具备跨平台兼容性，适配多种机器人臂和灵巧手。实验表明，该系统能显著提高灵巧操作任务的数据采集成功率与效率。
原文摘要 · Abstract (English)
Imitation learning has emerged as a powerful paradigm for robot skills learning. However, traditional data collection systems for dexterous manipulation face challenges, including a lack of balance between acquisition efficiency, consistency, and accuracy. To address these issues, we introduce Exo-ViHa, an innovative 3D-printed exoskeleton system that enables users to collect data from a first-person perspective while providing real-time haptic feedback. This system combines a 3D-printed modular structure with a slam camera, a motion capture glove, and a wrist-mounted camera. Various dexterous hands can be installed at the end, enabling it to simultaneously collect the posture of the end effector, hand movements, and visual data. By leveraging the first-person perspective and direct interaction, the exoskeleton enhances the task realism and haptic feedback, improving the consistency between demonstrations and actual robot deployments. In addition, it has cross-platform compatibility with various robotic arms and dexterous hands. Experiments show that the system can significantly improve the success rate and efficiency of data collection for dexterous manipulation tasks.
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