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首页> 外文期刊>Arabian Journal for Science and Engineering >Hybridization of Kidney‑Inspired and Sine–Cosine Algorithm for Multi‑robot Path Planning
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Hybridization of Kidney‑Inspired and Sine–Cosine Algorithm for Multi‑robot Path Planning

机译：肾脏启发与正弦余弦算法的多机器人路径规划混合

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摘要

A hybridization of kidney-inspired and sine–cosine algorithm has been proposed for a path planning of multiple mobilerobots in the environment where obstacles are either static or moveable. In this novel approach, each robot computes itscollision-free optimal path from their corresponding start position to goal position through hybridization of kidney-inspiredalgorithm (KA) and sine–cosine algorithm (SCA). The proposed KA–SCA employs the selection of subsequent optimal positionfor each robot from their current position by escaping the collision with dynamic obstacles and teammates. In the presentwork, SCA is used to accelerate the convergence rate of KA, to preserve a good equilibrium between the intensification anddiversification, and to compute an optimal path for each robot by minimizing the path distance, path deviation, number ofrotation for each robot, and running time required to reach their destination. Finally, the effectiveness and robustness of theproposed algorithm have been verified with the result of KA and SCA in the same environment. The result obtained fromthe real platform and simulation environment reveals that the proposed KA–SCA outperforms KA and SCA.
机译：已经提出了将肾脏启发和正弦余弦算法混合使用的方法，用于在障碍物是静态的或可移动的环境中的多个移动机器人的路径规划。在这种新颖的方法中，每个机器人都通过肾脏激励算法（KA）和正弦余弦算法（SCA）的混合计算出从其对应的起始位置到目标位置的无碰撞最佳路径。提出的KA–SCA通过避免与动态障碍物和队友的碰撞，从每个机器人的当前位置中选择后续的最佳位置。在当前的工作中，SCA用于加速KA的收敛速度，在增强和多样化之间保持良好的平衡，并通过最小化每个机器人的路径距离，路径偏差，转数以及每个机器人来计算最佳路径。到达目的地所需的运行时间。最后，在相同环境下，利用KA和SCA的结果，验证了所提算法的有效性和鲁棒性。从真实平台和仿真环境获得的结果表明，所提出的KA–SCA优于KA和SCA。

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