This paper presents a comparison of response times, route optimization, and graph complexity in path planning methods for autonomous mobile robots. The developments of Voronoi, Potential Fields, Probabilistic Roadmap and Decomposition in cells for navigation in the same environment are contrasted and validated for a variable number of obstacles. Evaluations show that the path generation method by Potential Fields improves navigation with respect to the shortest route obtained, the Rapidly Random Tree method generates graphs of less complexity and the Decomposition in cells method, performs with less response time and lower computational cost.

中文翻译：

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Desempeño en métodos de navegación autónoma para robots móviles

本文介绍了自主移动机器人路径规划方法中响应时间、路线优化和图形复杂性的比较。Voronoi、势场、概率路线图和分解在同一环境中用于导航的单元格的发展进行了对比和验证，以应对可变数量的障碍物。评估表明，基于势场的路径生成方法改进了获得的最短路线的导航，快速随机树方法生成的图形复杂度较低，而单元分解方法则具有更短的响应时间和更低的计算成本。