Give me scissors: Collision-Free Dual-Arm Surgical Assistive Robot for Instrument Delivery

TL;DR

This paper introduces a collision-free dual-arm surgical robot that uses vision-language models and real-time obstacle perception to autonomously deliver instruments safely and efficiently in dynamic surgical environments.

Contribution

It presents a novel robotic system combining vision-language guidance and real-time obstacle avoidance for autonomous surgical instrument delivery.

Findings

Achieves 83.33% success rate in instrument delivery

Maintains collision-free and smooth robot movements

Effectively operates in dynamic, obstacle-rich environments

Abstract

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/.