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| Main Authors: | , , , , , , |
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| Format: | Preprint |
| Published: |
2024
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2409.13905 |
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| _version_ | 1866909321957212160 |
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| author | Peiros, Elizabeth Joyce, Calvin Murugesan, Tarun Nguyen, Roger Fiorini, Isabella Galibut, Rizzi Yip, Michael C. |
| author_facet | Peiros, Elizabeth Joyce, Calvin Murugesan, Tarun Nguyen, Roger Fiorini, Isabella Galibut, Rizzi Yip, Michael C. |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2409_13905 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Haptic Shoulder for Rendering Biomechanically Accurate Joint Limits for Human-Robot Physical Interactions Peiros, Elizabeth Joyce, Calvin Murugesan, Tarun Nguyen, Roger Fiorini, Isabella Galibut, Rizzi Yip, Michael C. Robotics 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. |
| title | Haptic Shoulder for Rendering Biomechanically Accurate Joint Limits for Human-Robot Physical Interactions |
| topic | Robotics |
| url | https://arxiv.org/abs/2409.13905 |