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Multi-Path Planning for Autonomous Navigation of Multiple Robots in a Shared Workspace with Humans

机译:与人共享工作空间中的多个机器人自主导航的多路径规划

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Path finding for multiple robots is one of most important problems in robotics when to find a way to move robots from their starting positions to reach their respective goals without collisions. However, in the case of a complex environment with the presence of humans and other unpredictable moving objects, fixing a single path to the goal may lead to a situation where there are a lot of obstacles on the planned path and the robots may fail to realise the moving plan. To address this issue, a new approach of using multiple path planning where each robot has different options to choose its path to the goal is introduced in this paper. The information about planned moving paths are shared among the robots in the working domain, combined with obstacle avoidance constraints in local ranges, and formulated as an optimisation problem. Solution of the problem leads to the optimal moving plans of robots. The effectiveness of the proposed approach is demonstrated by experimental results.
机译:当寻找一种方法来使机器人从其起始位置移动到各自的目标而不会发生碰撞时,多个机器人的路径查找是机器人技术中最重要的问题之一。但是,在存在人类和其他不可预测的移动物体的复杂环境中,将单条路径固定到目标可能会导致计划路径上存在许多障碍并且机器人可能无法意识到的情况搬家计划。为了解决这个问题,本文介绍了一种使用多路径规划的新方法,其中每个机器人都有不同的选项来选择其到达目标的路径。有关计划移动路径的信息在工作域中的机器人之间共享,并与局部范围内的避障约束相结合,并被表述为优化问题。问题的解决导致了机器人的最佳运动计划。实验结果证明了该方法的有效性。

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