Soft and Compliant Contact-Rich Hair Manipulation and Care

TL;DR

This paper introduces MOE-Hair, a soft robotic system for hair care tasks that emphasizes safety, effectiveness, and user comfort through innovative force sensing and control methods, demonstrating advantages over rigid systems.

Contribution

The paper presents a novel soft robot end-effector with integrated visual and force sensing for contact-rich hair manipulation, improving safety and force estimation accuracy.

Findings

MOE-Hair achieves effective hair grasping with less force than rigid grippers.

The force estimation method reduces sensing errors by up to 60.1%.

Participants preferred MOE-Hair for comfort and effectiveness.

Abstract

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.