文章基本信息

标题：A Novel Global Path Planning Method for Mobile Robots Based on Teaching-Learning-Based Optimization
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作者：Zongsheng Wu ; Weiping Fu ; Ru Xue 等
期刊名称：Information
电子版ISSN：2078-2489
出版年度：2016
卷号：7
期号：3
页码：39-49
DOI：10.3390/info7030039
出版社：MDPI Publishing
摘要：The Teaching-Learning-Based Optimization (TLBO) algorithm has been proposed in recent years. It is a new swarm intelligence optimization algorithm simulating the teaching-learning phenomenon of a classroom. In this paper, a novel global path planning method for mobile robots is presented, which is based on an improved TLBO algorithm called Nonlinear Inertia Weighted Teaching-Learning-Based Optimization (NIWTLBO) algorithm in our previous work. Firstly, the NIWTLBO algorithm is introduced. Then, a new map model of the path between start-point and goal-point is built by coordinate system transformation. Lastly, utilizing the NIWTLBO algorithm, the objective function of the path is optimized; thus, a global optimal path is obtained. The simulation experiment results show that the proposed method has a faster convergence rate and higher accuracy in searching for the path than the basic TLBO and some other algorithms as well, and it can effectively solve the optimization problem for mobile robot global path planning.
关键词：mobile robot; path planning; optimization methods; teaching-learning-based optimization (TLBO) mobile robot ; path planning ; optimization methods ; teaching-learning-based optimization (TLBO)