SIMS: Surgeon-Intention-driven Motion Scaling for Efficient and Precise Teleoperation
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arXiv
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| Format: | Preprint |
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2025
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| author | Yoon, Jeonghyeon Park, Sanghyeok Park, Hyojae Kim, Cholin Yip, Michael C. Hwang, Minho |
| author_facet | Yoon, Jeonghyeon Park, Sanghyeok Park, Hyojae Kim, Cholin Yip, Michael C. Hwang, Minho |
| contents | Telerobotic surgery often relies on a fixed motion scaling factor (MSF) to map the surgeon's hand motions to robotic instruments, but this introduces a trade-off between precision and efficiency: small MSF enables delicate manipulation but slows large movements, while large MSF accelerates transfer at the cost of accuracy. We propose a Surgeon-Intention driven Motion Scaling (SIMS) system, which dynamically adjusts MSF in real time based solely on kinematic cues. SIMS extracts linear speed, tool motion alignment, and dual-arm coordination features to classify motion intent via fuzzy C-means clustering and applies confidence-based updates independently for both arms. In a user study (n=10, three surgical training tasks) conducted on the da Vinci Research Kit, SIMS significantly reduced collisions (mean reduction of 83%), lowered mental and physical workload, and maintained task completion efficiency compared to fixed MSF. These findings demonstrate that SIMS is a practical and lightweight approach for safer, more efficient, and user-adaptive telesurgical control. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2503_01216 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | SIMS: Surgeon-Intention-driven Motion Scaling for Efficient and Precise Teleoperation Yoon, Jeonghyeon Park, Sanghyeok Park, Hyojae Kim, Cholin Yip, Michael C. Hwang, Minho Robotics Telerobotic surgery often relies on a fixed motion scaling factor (MSF) to map the surgeon's hand motions to robotic instruments, but this introduces a trade-off between precision and efficiency: small MSF enables delicate manipulation but slows large movements, while large MSF accelerates transfer at the cost of accuracy. We propose a Surgeon-Intention driven Motion Scaling (SIMS) system, which dynamically adjusts MSF in real time based solely on kinematic cues. SIMS extracts linear speed, tool motion alignment, and dual-arm coordination features to classify motion intent via fuzzy C-means clustering and applies confidence-based updates independently for both arms. In a user study (n=10, three surgical training tasks) conducted on the da Vinci Research Kit, SIMS significantly reduced collisions (mean reduction of 83%), lowered mental and physical workload, and maintained task completion efficiency compared to fixed MSF. These findings demonstrate that SIMS is a practical and lightweight approach for safer, more efficient, and user-adaptive telesurgical control. |
| title | SIMS: Surgeon-Intention-driven Motion Scaling for Efficient and Precise Teleoperation |
| topic | Robotics |
| url | https://arxiv.org/abs/2503.01216 |