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A Practical Framework for Cleaning Robots

机译:清洁机器人的实用框架

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This paper presents an extension to the pattern-based genetic algorithm for multiple cleaning robots to achieve complete coverage path planning in an unknown environment. The extension is formulated in the form of a framework which consists of four phases. The phases are scouting, task distribution, cleaning, and confirmation. The scouting phase allows the robots to scout in the initially unknown floor plan. The task distribution phase distributes cleaning tasks to multiple robots. The cleaning phase uses the pattern-based genetic algorithm with an added function to cater to unforeseen obstacles. The confirmation phaserecleans all the tiles. The performance of our proposed approach have been evaluated with six different floor plans through computer experiments. The cleaning phase performs better than the generic pattern-based genetic algorithm approach.
机译:本文介绍了多种清洁机器人的基于模式的遗传算法的扩展,以实现未知环境中的完整覆盖路径规划。扩展以框架的形式制定,该框架由四个阶段组成。阶段是侦察,任务分配,清洁和确认。侦察阶段允许机器人在最初未知的平面图中侦察侦察。任务分发阶段将清洁任务分配给多个机器人。清洁阶段使用基于模式的遗传算法来迎合不可预见的障碍物的附加功能。确认phaserecleans所有瓷砖。通过计算机实验,已经通过六种不同的楼层计划进行了拟议方法的表现。清洁阶段比普通模式的遗传算法方法更好地执行。

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