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Mobile robot path planning by new structured multi-objective genetic algorithm

机译:新结构多目标遗传算法的移动机器人路径规划

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摘要

Path planning problem of mobile robot is one that has intrigued and has received much attention throughout the history of robotics, since it is at the essence of what a mobile robot needs to be considered truly “autonomous”. A mobile robot must be able to find collision-free paths to move from one location to another, and in order to truly show a level of intelligence these paths must be optimized under some criteria that are important to the robot, working space and given problem. In this paper we propose a new structured multi-objective genetic algorithm to solve this problem. In our method we explore only valid search space that results in a smaller search space. Also we show the defect of earlier evaluation function and present a new evaluation function. To evaluate our idea we compare our evaluation function with other ones and show the performance of our method. Experiments show the ability of our method in finding best paths with low generation and population.
机译:移动机器人的路径规划问题是一个在整个机器人历史上感兴趣,并且在机器人历史上受到了很多关注,因为它是移动机器人需要被视为真正“自主”的本质。移动机器人必须能够找到从一个位置移动到另一个位置的碰撞路径,以便真正显示智能水平,这些路径必须在对机器人,工作空间和给定问题重要的一些标准下进行优化。在本文中,我们提出了一种新的结构化多目标遗传算法来解决这个问题。在我们的方法中,我们只探索有效的搜索空间,导致较小的搜索空间。此外,我们还显示了早期评估功能的缺陷,并提出了新的评估功能。为了评估我们的想法,我们将评估功能与其他人进行比较并显示我们方法的性能。实验表明我们的方法在找到低生成和人口的最佳路径方面的能力。

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