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Cooperation of multi-robots for obstacle avoidance in clutter environment using differential evolutionary algorithm

机译:基于微分进化算法的多机器人协同在杂物环境下避障

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This paper deliberates an optimal navigation path for multiple mobile robots using the differential evolution (DE) algorithm. The algorithm determines the next position of every robots by considering the goal position and nearest obstacles coordinates. DE algorithm uses different popular vectors for balancing the exploration and exploitations to provide a nearly optimal solution. To get an optimized path from starting position of the robot to a target position, a sequence of the intermediate positions are taken into consideration through the algorithm. In each position, the robot predicts the position of obstacles before determining the next position. The simulation result unveils that, the proposed algorithm generates a safe, optimised and smooth path in an unknown environment.
机译:本文使用差分进化(DE)算法为多个移动机器人研究了一条最优的导航路径。该算法通过考虑目标位置和最近的障碍物坐标来确定每个机器人的下一个位置。 DE算法使用不同的流行矢量来平衡探索和开发,以提供近乎最佳的解决方案。为了获得从机器人的起始位置到目标位置的最佳路径,通过算法考虑了一系列中间位置。在每个位置,机器人都会在确定下一个位置之前预测障碍物的位置。仿真结果表明,该算法在未知环境下可以生成安全,优化,平滑的路径。

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