The path planning of cleaner robot for coverage region using Genetic Algorithms

Mohamed Amine Yakoubi, Mohamed Tayeb Laskri
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引用次数: 75

Abstract

The vacuum cleaner robot should have a mechanism such as the artificial intelligence to solve the problem of cleaning the entire environment areas taking into account some factors such as the number of turns and the length of the trajectory. This robot’s mechanism or task is known as the path planning of coverage region (PPCR). In this paper, to resolve the problem of PPCR in a room environment, we propose an evolutionary approach. The latter is based on Genetic Algorithms (GA) which, consist of several steps to get the solutions. Each gene represents the robot position and some of chromosomes represent also the mini-path. In addition, this algorithm helps the robot to pass through every part of the environment by avoiding obstacles using different sensors. The results of simulation and comparison studies demonstrate the effectiveness and efficiency of the proposed approach.

基于遗传算法的清扫机器人覆盖区域路径规划
真空吸尘器机器人应具有人工智能等机制来解决整个环境区域的清洁问题,同时考虑到旋转次数和轨迹长度等因素。这种机器人的机制或任务被称为覆盖区域路径规划(PPCR)。在本文中,为了解决PPCR在房间环境中的问题,我们提出了一个进化的方法。后者是基于遗传算法(GA),由几个步骤组成的解决方案。每个基因代表机器人的位置,一些染色体也代表迷你路径。此外,该算法通过使用不同的传感器避开障碍物,帮助机器人通过环境的每个部分。仿真和对比研究的结果证明了该方法的有效性和高效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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