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Main Authors: Luo, Xuejin, Sun, Shiquan, Zhang, Runshi, Zhang, Ruizhi, Wang, Junchen
Format: Preprint
Published: 2026
Subjects:
Online Access:https://arxiv.org/abs/2603.02553
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author Luo, Xuejin
Sun, Shiquan
Zhang, Runshi
Zhang, Ruizhi
Wang, Junchen
author_facet Luo, Xuejin
Sun, Shiquan
Zhang, Runshi
Zhang, Ruizhi
Wang, Junchen
contents During surgery, scrub nurses are required to frequently deliver surgical instruments to surgeons, which can lead to physical fatigue and decreased focus. Robotic scrub nurses provide a promising solution that can replace repetitive tasks and enhance efficiency. Existing research on robotic scrub nurses relies on predefined paths for instrument delivery, which limits their generalizability and poses safety risks in dynamic environments. To address these challenges, we present a collision-free dual-arm surgical assistive robot capable of performing instrument delivery. A vision-language model is utilized to automatically generate the robot's grasping and delivery trajectories in a zero-shot manner based on surgeons' instructions. A real-time obstacle minimum distance perception method is proposed and integrated into a unified quadratic programming framework. This framework ensures reactive obstacle avoidance and self-collision prevention during the dual-arm robot's autonomous movement in dynamic environments. Extensive experimental validations demonstrate that the proposed robotic system achieves an 83.33% success rate in surgical instrument delivery while maintaining smooth, collision-free movement throughout all trials. The project page and source code are available at https://give-me-scissors.github.io/.
format Preprint
id arxiv_https___arxiv_org_abs_2603_02553
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Give me scissors: Collision-Free Dual-Arm Surgical Assistive Robot for Instrument Delivery
Luo, Xuejin
Sun, Shiquan
Zhang, Runshi
Zhang, Ruizhi
Wang, Junchen
Robotics
Computer Vision and Pattern Recognition
Human-Computer Interaction
Machine Learning
During surgery, scrub nurses are required to frequently deliver surgical instruments to surgeons, which can lead to physical fatigue and decreased focus. Robotic scrub nurses provide a promising solution that can replace repetitive tasks and enhance efficiency. Existing research on robotic scrub nurses relies on predefined paths for instrument delivery, which limits their generalizability and poses safety risks in dynamic environments. To address these challenges, we present a collision-free dual-arm surgical assistive robot capable of performing instrument delivery. A vision-language model is utilized to automatically generate the robot's grasping and delivery trajectories in a zero-shot manner based on surgeons' instructions. A real-time obstacle minimum distance perception method is proposed and integrated into a unified quadratic programming framework. This framework ensures reactive obstacle avoidance and self-collision prevention during the dual-arm robot's autonomous movement in dynamic environments. Extensive experimental validations demonstrate that the proposed robotic system achieves an 83.33% success rate in surgical instrument delivery while maintaining smooth, collision-free movement throughout all trials. The project page and source code are available at https://give-me-scissors.github.io/.
title Give me scissors: Collision-Free Dual-Arm Surgical Assistive Robot for Instrument Delivery
topic Robotics
Computer Vision and Pattern Recognition
Human-Computer Interaction
Machine Learning
url https://arxiv.org/abs/2603.02553