This paper presents a novel solution of coverage path planning for robotic mowing applications. The planning algorithm is based on the Boustrophedon motions and the rapid Voronoi diagram. The coordinate conversion and the sweeping vector is defined by minimum bounding box and the Voronoi travel paths are designed to reduce the computational cost and execution time compared to conventional heuristic methods. The tracked path is controlled via dynamic feedback in standard lawn mowing robots under robot operating system (ROS). Within ROS, the information exchanging among different tasks of both extensive simulation cases and experimental field tests can be conducted easily. When meeting unknown obstacles, the proposed algorithm can re-plan its paths dynamically. The performance of the proposed algorithm is compared to several conventional coverage algorithms in terms of time efficiency, coverage, repetition, and robustness with respect to both concave and convex shapes. The field tests are conducted to demonstrate that the applicability of the sensor fusion and robustness of the proposed algorithm for the complete coverage tasks by robotic mowers.

本文提出了一种适用于机器人割草应用的覆盖路径规划的新解决方案。规划算法基于 Boustrophedon 运动和快速 Voronoi 图。坐标转换和扫描向量由最小边界框定义，与传统启发式方法相比，Voronoi 行进路径旨在减少计算成本和执行时间。跟踪路径通过机器人操作系统 (ROS) 下标准割草机器人的动态反馈控制。在 ROS 中，可以轻松进行广泛的模拟案例和实验现场测试的不同任务之间的信息交换。当遇到未知障碍时，所提出的算法可以动态重新规划其路径。在时间效率、覆盖范围、重复性和关于凹凸形状的鲁棒性方面，将所提出的算法的性能与几种传统覆盖算法进行了比较。进行现场测试以证明传感器融合的适用性和所提出的算法对机器人割草机的完整覆盖任务的鲁棒性。