无需预设路径的双臂手术机器人，能听懂指令自动送器械且全程避障。
Give me scissors: Collision-Free Dual-Arm Surgical Assistive Robot for Instrument Delivery
- 用视觉语言模型解析医生指令，零样本生成抓取与运送轨迹。
- 实测83.33%成功率，所有实验均实现无碰撞、无自碰撞运动。
- 适合临床手术辅助场景，尤其适用于动态复杂环境下的自动化配送。
手术中刷手护士需频繁为外科医生递送器械，易导致体力疲劳和注意力下降。机器人刷手护士可替代重复性任务并提升效率。现有研究依赖预设路径进行器械递送，限制了泛化能力，并在动态环境中存在安全风险。为此，本文提出一种无碰撞双臂手术辅助机器人，能够完成器械递送任务。采用视觉语言模型，基于外科医生指令以零样本方式自动生成机器人的抓取与递送轨迹。提出一种实时障碍物最小距离感知方法，并集成至统一的二次规划框架中，确保在动态环境中双臂机器人自主运动时具备反应式避障与自碰撞预防能力。大量实验验证表明，该系统在器械递送任务中达到83.33%的成功率，且所有试验均保持平滑、无碰撞运动。项目主页与源代码见https://give-me-scissors.github.io/。
原文摘要 · Abstract (English)
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/.
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