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An online complete coverage approach for a team of robots in unknown environments

机译:针对未知环境中的机器人团队的在线完整覆盖方法

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This paper presents a novel approach to deal with the online complete coverage problem for a team of robots in unknown environments. In our approach each robot covers an unvisited region using a single boustrophedon motion until a robot reaches an ending point, which is surrounded by covered positions or obstacles. At the ending point the robot detects backtracking points based on the accumulated knowledge, plans the shortest backtracking path to the next starting point based on the proposed Theta* with multi-goals. Then, it follows the planed path to the next starting point to cover the next unvisited region. The robot team finishes the coverage task when no backtracking point is detected. Computer simulations show that our proposed approach is efficient for the complete coverage task of a robot team in terms of the coverage rate and the coverage path length.
机译:本文提出了一种新颖的方法来处理未知环境中的一组机器人的在线完全覆盖问题。在我们的方法中,每个机器人都使用一次自滑运动覆盖一个未被访问的区域,直到机器人到达终点为止,该终点被被遮盖的位置或障碍物所包围。在结束时,机器人会基于积累的知识来检测回溯点,并根据拟议的Theta *和多目标计划最短的回溯路径到下一个起点。然后,它沿着计划的路径到达下一个起点,以覆盖下一个未访问的区域。当未检测到回溯点时,机器人团队将完成覆盖任务。计算机仿真表明,我们提出的方法对于覆盖率和覆盖路径长度的机器人团队的完整覆盖任务是有效的。

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