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Multi-robot Task Allocation Using Island Model Genetic Algorithm ?

机译:使用岛式模型遗传算法的多机器人任务分配

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Mobile robots have been used in several areas as agriculture, vigilance, and indoor transportation in factories and warehouses. The warehouses’ efficiency is directly related to transportation in the order picking process. Using mobile robots can improve transportation efficiency when associated with optimized task allocation. This paper shows a method, using the island model genetic algorithm, to allocate tasks with deadlines in multi-robot systems where mobile robots have different payloads and speed capacities. The approach’s performance was evaluated by varying parameters of the algorithm and the size of the task set, and the robot set involved in the allocation process. The performance criteria adopted were success rate in allocating all tasks, percentage of assigned tasks in non-complete solutions, and obtaining a complete solution. The results have shown that the method brings a more significant number of complete solutions in sets with a small and medium number of tasks. Besides that, the solutions obtained meets deadlines and show energy consumption reduction.
机译:移动机器人已在农业,警惕和仓库中的农业,警惕和室内运输中使用。仓库的效率与订单采摘过程中的运输直接相关。使用移动机器人可以在优化任务分配相关时提高运输效率。本文显示了一种使用岛模型遗传算法的方法,将任务分配具有多机器人系统中的截止日期,其中移动机器人具有不同的有效载荷和速度。通过改变算法的参数和任务集的大小以及分配过程中涉及的机器人组来评估该方法的性能。采用的性能标准是分配所有任务,非完整解决方案中指定任务的百分比以及获得完整解决方案的成功率。结果表明,该方法以小且中等任务的组件带来了更大数量的完整解决方案。除此之外,获得的溶液符合最后期限并显示出能耗降低。

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