为冗余机械臂设计高效全覆盖路径规划方法
Coverage Path Planning for Redundant Manipulators using Generalized Spanning Trees
- 基于广义生成树构建多解选择框架，优化配置决策
- 离线法降低计算时间与关节运动量，线上法支持动态环境实时规划
- 适合需要高质量轨迹的工业表面作业场景
使用任务冗余机械臂进行表面覆盖具有挑战性，因为每个表面点可能对应多个逆运动学（IK）解，且配置选择会显著影响运动质量。本文通过离线与在线联合生成树覆盖（JSTC）算法，将经典生成树覆盖（STC）方法扩展至冗余机械臂。离线JSTC在每个网格单元中采样多个逆运动学解，并将问题建模为广义最小生成树（GMST），为每单元选择一个配置并追踪生成树以获得无重复访问的覆盖路径。在线JSTC则通过可行性与代价评估，增量式扩展与回溯生成树，应对动态网格更新。仿真结果表明，离线JSTC相比其他方法显著减少计算时间、重构次数与关节运动量；在线JSTC在动态场景中实现快速单步规划。
原文摘要 · Abstract (English)
Surface coverage with task-redundant manipulators is challenging because each surface point may admit multiple inverse kinematics (IK) solutions, and configuration choices strongly affect motion quality. This paper extends the classical Spanning Tree Coverage (STC) method to redundant manipulators through offline and online Joint Spanning Tree Coverage (JSTC) algorithms. Offline JSTC samples multiple Inverse Kinematics (IK) solutions per grid cell and formulates the problem as a Generalized Minimum Spanning Tree (GMST), selecting one configuration per cell and tracing the resulting tree to obtain a non-revisiting coverage path. Online JSTC incrementally expands and backtracks a spanning tree with feasibility and cost evaluation while handling dynamic grid updates. Simulation results show that offline JSTC reduces computation time, reconfigurations, and joint motion compared to other methods, while online JSTC achieves fast per-step planning in dynamic scenarios.
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