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Autonomous RCM-less endoscope control: integrating force-based pivoting with deep learning visual servoing – Scientific Reports
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Scientific Reports (2026) Cite this article
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Abstract
Robotic endoscope holders improve visual stability, yet enforcing a fixed remote center of motion (RCM) often induces lateral interaction forces due to fulcrum drift. This study proposes an autonomous guidance framework combining deep learning–based visual servoing with force-based pivoting to track surgical instruments while minimizing interaction forces, without a fixed geometric RCM. To test this, a UR3e manipulator with an integrated force/torque sensor controlled a laparoscope in a pelvitrainer. Instruments were localized using a fine-tuned YOLOv11n on 3,695 annotated frames. The detected tools’ centroids drove a hysteresis-based visual servoing law with jerk-limited planning, while an admittance-based controller generated angular motion from measured forces. Performance was assessed in continuous tracking and step-response tasks, comparing fixed-RCM with the proposed pivoting approach. The localization model achieved 0.91–0.93 precision, 0.83–0.90 mAP, and 28 FPS on a CPU. Visual servoing re-centered targets in 98.8% of transitions (median recovery: 2.60 s). Force-based pivoting significantly outperformed fixed-RCM control, reducing median interaction forces from 2.35 to 0.19 N. Integrating CNN-driven servoing with force-based pivoting enables autonomous guidance that preserves visual stability while substantially reducing interaction forces. By eliminating fixed RCM assumptions, this framework offers a safer, more adaptive alternative for robotic camera assistance.
Funding
This project has been funded by the Spanish Ministry of Science, Innovation and Universities through PID2022-138206OB-C33.
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Fontúrbel, C., Cisnal, A., Benavides-Cobos, D. et al. Autonomous RCM-less endoscope control: integrating force-based pivoting with deep learning visual servoing. Sci Rep (2026). https://doi.org/10.1038/s41598-026-54550-9
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DOI: https://doi.org/10.1038/s41598-026-54550-9
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