软体机器人实现安全柔顺的头发护理，力控精度显著提升。
Soft and Compliant Contact-Rich Hair Manipulation and Care
- 用腱驱动软机械手+视觉形变感知实现安全接触
- 抓发力度比刚性夹具低，力估误差降低超60%
- 适合老年护理、行动不便者，注重舒适与精准
护发机器人可缓解养老人力短缺问题，帮助行动受限者维护头发相关的自我认同。本文提出MOE-Hair系统，实现头部轻拍、手指梳头和抓发三项护理任务。该系统采用腱驱动软体末端执行器（MOE）并配备腕部安装的RGBD相机，利用机械柔性保障安全，并通过形变视觉信息实现力觉感知。在搭载力传感器的假人头测试中，MOE在抓发效果相当的前提下，施加的力显著低于刚性夹具。其创新的力估计算法融合视觉形变数据与驱动器腱张力，相比仅依赖驱动电流和仅依赖深度图像的基线方法，力估误差分别降低60.1%和20.3%。12名用户参与的实验表明，参与者在舒适度、有效性及力控制适配性上对MOE-Hair有统计学显著偏好。结果表明，软体机器人在高接触密度护理任务中具有独特优势，同时凸显了精确力控在柔性系统中的关键作用。
原文摘要 · Abstract (English)
Hair care robots can help address labor shortages in elderly care while enabling those with limited mobility to maintain their hair-related identity. We present MOE-Hair, a soft robot system that performs three hair-care tasks: head patting, finger combing, and hair grasping. The system features a tendon-driven soft robot end-effector (MOE) with a wrist-mounted RGBD camera, leveraging both mechanical compliance for safety and visual force sensing through deformation. In testing with a force-sensorized mannequin head, MOE achieved comparable hair-grasping effectiveness while applying significantly less force than rigid grippers. Our novel force estimation method combines visual deformation data and tendon tensions from actuators to infer applied forces, reducing sensing errors by up to 60.1% and 20.3% compared to actuator current load-only and depth image-only baselines, respectively. A user study with 12 participants demonstrated statistically significant preferences for MOE-Hair over a baseline system in terms of comfort, effectiveness, and appropriate force application. These results demonstrate the unique advantages of soft robots in contact-rich hair-care tasks, while highlighting the importance of precise force control despite the inherent compliance of the system.
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