清洁机器人的实用框架

Wen-Mau Chong, Chien-Le Goh, Yoon-Teck Bau
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引用次数: 5

摘要

本文对基于模式的遗传算法进行了扩展,实现了多清扫机器人在未知环境下的全覆盖路径规划。扩展以框架的形式制定,该框架由四个阶段组成。这些阶段是侦查、任务分配、清理和确认。侦察阶段允许机器人在最初未知的平面图中进行侦察。任务分配阶段将清洁任务分配给多个机器人。清理阶段使用基于模式的遗传算法,并添加了一个功能来满足不可预见的障碍。确认阶段清除所有的tile。通过计算机实验,对六种不同的平面图进行了性能评估。清理阶段的性能优于基于通用模式的遗传算法方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Practical Framework for Cleaning Robots
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.
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