Mobile robot navigation control using recurrent fuzzy cerebellar model articulation controller based on improved dynamic artificial bee colony

In this study, an efficient navigation control method of mobile robot is proposed. The proposed navigation control method consists of behavior manager, toward goal behavior, and wall-following behavior. According to the relative position between the mobile robot and the environment, the behavior man...

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Bibliographic Details
Main Authors: Lingling Li, Cheng-Jian Lin, Mei-Ling Huang, Shye-Chorng Kuo, Yun-Ren Chen
Format: Article
Language:English
Published: SAGE Publishing 2016-11-01
Series:Advances in Mechanical Engineering
Online Access:https://doi.org/10.1177/1687814016681234
Description
Summary:In this study, an efficient navigation control method of mobile robot is proposed. The proposed navigation control method consists of behavior manager, toward goal behavior, and wall-following behavior. According to the relative position between the mobile robot and the environment, the behavior manager switches to determine toward goal behavior or wall-following behavior of mobile robot. A novel recurrent fuzzy cerebellar model articulation controller based on an improved dynamic artificial bee colony is proposed for performing wall-following control of mobile robot. The proposed improved dynamic artificial bee colony algorithm uses the sharing mechanism and the dynamic identity update to improve the performance of optimization. A reinforcement learning method is adopted to train the wall-following control of mobile robot. Experimental results show that the proposed method obtains a better navigation control than other methods in unknown environment.
ISSN:1687-8140