文章基本信息

标题：Mobile Robot Path Planning Using Polyclonal-Based Artificial Immune Network
本地全文：下载
作者：Lixia Deng ; Xin Ma ; Jason Gu 等
期刊名称：Journal of Control Science and Engineering
印刷版ISSN：1687-5249
电子版ISSN：1687-5257
出版年度：2013
卷号：2013
DOI：10.1155/2013/416715
出版社：Hindawi Publishing Corporation
摘要：Polyclonal based artificial immune network (PC-AIN) is utilized for mobile robot path planning. Artificial immune network (AIN) has been widely used in optimizing the navigation path with the strong searching ability and learning ability. However, artificial immune network exists as a problem of immature convergence which some or all individuals tend to the same extreme value in the solution space. Thus, polyclonal-based artificial immune network algorithm is proposed to solve the problem of immature convergence in complex unknown static environment. Immunity polyclonal algorithm (IPCA) increases the diversity of antibodies which tend to the same extreme value and finally selects the antibody with highest concentration. Meanwhile, immunity polyclonal algorithm effectively solves the problem of local minima caused by artificial potential field during the structure of parameter in artificial immune network. Extensive experiments show that the proposed method not only solves immature convergence problem of artificial immune network but also overcomes local minima problem of artificial potential field. So, mobile robot can avoid obstacles, escape traps, and reach the goal with optimum path and faster convergence speed.