提出分层框架，让手术机器人高效避障并保持操作精度。
A hierarchical framework for collision avoidance in robot-assisted minimally invasive surgery
- 用分层二次规划整合多任务约束，动态调整优先级。
- 仿真验证可应对静态、动态障碍及器械间碰撞。
- 适合需高安全性的主从式微创手术机器人系统。
微创手术（MIS）得益于机器人系统带来的更高精度和灵活性，但在动态杂乱环境中保障安全仍是挑战。本文提出一种新型分层框架，用于微创手术中的碰撞避免。该框架整合了多个任务：维持远端运动中心（RCM）约束、跟踪期望工具位姿、避免碰撞、优化操作性以及遵守关节限位。所提方法采用分层二次规划（HQP）无缝管理这些约束，并支持任务优先级的平滑切换，以实现碰撞避免。通过模拟场景的实验验证表明，该框架在处理包含静态与动态障碍物、以及器械间碰撞的多种情况时表现出鲁棒性和有效性。
原文摘要 · Abstract (English)
Minimally invasive surgery (MIS) procedures benefit significantly from robotic systems due to their improved precision and dexterity. However, ensuring safety in these dynamic and cluttered environments is an ongoing challenge. This paper proposes a novel hierarchical framework for collision avoidance in MIS. This framework integrates multiple tasks, including maintaining the Remote Center of Motion (RCM) constraint, tracking desired tool poses, avoiding collisions, optimizing manipulability, and adhering to joint limits. The proposed approach utilizes Hierarchical Quadratic Programming (HQP) to seamlessly manage these constraints while enabling smooth transitions between task priorities for collision avoidance. Experimental validation through simulated scenarios demonstrates the framework's robustness and effectiveness in handling diverse scenarios involving static and dynamic obstacles, as well as inter-tool collisions.
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