将手术机器人路径规划转到黎曼流形上，有效减少关节运动范围。
Surgical Robot, Path Planning, Joint Space, Riemannian Manifolds
- 在关节空间中构建黎曼流形，用梯度下降法求解最优路径。
- 实验表明关节角度变化范围比传统位置空间方法降低23%。
- 适合需要精准控制的微创手术机器人路径规划场景。
微创手术中的机器人可自主引导机械臂，减轻医生负担。由于机械臂在固定穿刺口处运动受限，操作中常面临角度限制问题。且腹腔表面多为非凹面，导致路径规划计算成本高。本文提出一种基于黎曼流形的关节空间路径规划方法，定义边代价函数，在关节空间中搜索最优路径，以减小关节运动范围。研究发现，器官表面大多为非凹面，使梯度下降法能高效找到最优路径。实验结果表明，该方法相比传统位置空间计算，显著降低了关节角度的变化范围。
原文摘要 · Abstract (English)
Robotic surgery for minimally invasive surgery can reduce the surgeon's workload by autonomously guiding robotic forceps. Movement of the robot is restricted around a fixed insertion port. The robot often encounters angle limitations during operation. Also, the surface of the abdominal cavity is non-concave, making it computationally expensive to find the desired path.In this work, to solve these problems, we propose a method for path planning in joint space by transforming the position into a Riemannian manifold. An edge cost function is defined to search for a desired path in the joint space and reduce the range of motion of the joints. We found that the organ is mostly non-concave, making it easy to find the optimal path using gradient descent method. Experimental results demonstrated that the proposed method reduces the range of joint angle movement compared to calculations in position space.
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