生体力学に基づく関節可動域を再現する触覚肩部デバイス：人とロボットの物理的インタラクションに向けて
Haptic Shoulder for Rendering Biomechanically Accurate Joint Limits for Human-Robot Physical Interactions
人間の肩の動きと力覚を再現する安価なオープンソースデバイスSHULDRDを開発し、人を被験者にせずにロボットの物理支援計画を安全に評価できるようにした。
著者: Elizabeth Peiros, Calvin Joyce, Tarun Murugesan, Roger Nguyen, Isabella Fiorini, Rizzi Galibut, Michael C. Yip
分類: cs.RO
原文アブストラクト
Human-robot physical interaction (pHRI) is a rapidly evolving research field with significant implications for physical therapy, search and rescue, and telemedicine. However, a major challenge lies in accurately understanding human constraints and safety in human-robot physical experiments without an IRB and physical human experiments. Concerns regarding human studies include safety concerns, repeatability, and scalability of the number and diversity of participants. This paper examines whether a physical approximation can serve as a stand-in for human subjects to enhance robot autonomy for physical assistance. This paper introduces the SHULDRD (Shoulder Haptic Universal Limb Dynamic Repositioning Device), an economical and anatomically similar device designed for real-time testing and deployment of pHRI planning tasks onto robots in the real world. SHULDRD replicates human shoulder motion, providing crucial force feedback and safety data. The device's open-source CAD and software facilitate easy construction and use, ensuring broad accessibility for researchers. By providing a flexible platform able to emulate infinite human subjects, ensure repeatable trials, and provide quantitative metrics to assess the effectiveness of the robotic intervention, SHULDRD aims to improve the safety and efficacy of human-robot physical interactions.
