利用机械臂冗余性，高效规划表面全覆盖路径。
Hierarchically Accelerated Coverage Path Planning for Redundant Manipulators
- 将覆盖路径规划建模为广义旅行商问题，分层简化图规模。
- 通过引导路径分步求解，显著降低关节空间计算成本。
- 适合需要精细表面操作的工业机器人应用。
许多机器人应用，如打磨、抛光、擦拭和传感器扫描，要求机械臂通过末端执行器精确覆盖表面。本文提出一种高效且有效的覆盖路径规划方法，利用机械臂的冗余性和任务容差，在关节空间中最小化代价。我们将问题建模为广义旅行商问题，并通过分层方式逐步缩减图规模。策略是先识别大致覆盖表面的引导路径，再通过求解一系列更小的问题加速计算。我们通过仿真实验和物理机器人演示验证了该方法的有效性。
原文摘要 · Abstract (English)
Many robotic applications, such as sanding, polishing, wiping and sensor scanning, require a manipulator to dexterously cover a surface using its end-effector. In this paper, we provide an efficient and effective coverage path planning approach that leverages a manipulator's redundancy and task tolerances to minimize costs in joint space. We formulate the problem as a Generalized Traveling Salesman Problem and hierarchically streamline the graph size. Our strategy is to identify guide paths that roughly cover the surface and accelerate the computation by solving a sequence of smaller problems. We demonstrate the effectiveness of our method through a simulation experiment and an illustrative demonstration using a physical robot.
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