用S-RRT*算法实现柔韧机械臂避障路径规划，兼顾精度与效率。
S-RRT*-based Obstacle Avoidance Autonomous Motion Planner for Continuum-rigid Manipulator
- 结合S-RRT*与逆瞬时运动学，生成平滑且避障的关节轨迹。
- 在复杂环境中成功规划路径，计算时间优于同类方法。
- 适合医疗手术、工业精密操作等高自由度机械臂场景。
连续体机器人结构紧凑、灵活，适用于工业和医疗手术。快速探索随机树（RRT）是一种高效的路径规划方法，其变体S-RRT可为末端执行器生成平滑可行路径。通过结合逆瞬时运动学（IIK），可实现连续体机械臂的完整运动规划。由于连续体机械臂具有高自由度，其逆运动学中的零空间可用于避障。本文提出一种基于S-RRT*的新方法，用于连续体-刚性机械臂的运动规划。利用IIK与零空间技术，生成连续的关节配置，不仅精确跟踪路径，还能有效避开障碍物。仿真结果表明，该方法在复杂环境中能高效完成运动规划与避障，生成高质量的末端路径。相较类似IIK方法，本方法计算时间更优。
原文摘要 · Abstract (English)
Continuum robots are compact and flexible, making them suitable for use in the industries and in medical surgeries. Rapidly-exploring random trees (RRT) are a highly efficient path planning method, and its variant, S-RRT, can generate smooth feasible paths for the end-effector. By combining RRT with inverse instantaneous kinematics (IIK), complete motion planning for the continuum arm can be achieved. Due to the high degrees of freedom of continuum arms, the null space in IIK can be utilized for obstacle avoidance. In this work, we propose a novel approach that uses the S-RRT* algorithm to create paths for the continuum-rigid manipulator. By employing IIK and null space techniques, continuous joint configurations are generated that not only track the path but also enable obstacle avoidance. Simulation results demonstrate that our method effectively handles motion planning and obstacle avoidance while generating high-quality end-effector paths in complex environments. Furthermore, compared to similar IIK methods, our approach exhibits superior computation time.
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