In this study, an efficient navigation control method of mobile robot is proposed. The proposed navigation control\nmethod consists of behavior manager, toward goal behavior, and wall-following behavior. According to the relative position\nbetween the mobile robot and the environment, the behavior manager switches to determine toward goal behavior\nor wall-following behavior of mobile robot. A novel recurrent fuzzy cerebellar model articulation controller based on an\nimproved dynamic artificial bee colony is proposed for performing wall-following control of mobile robot. The proposed\nimproved dynamic artificial bee colony algorithm uses the sharing mechanism and the dynamic identity update to\nimprove the performance of optimization. A reinforcement learning method is adopted to train the wall-following control\nof mobile robot. Experimental results show that the proposed method obtains a better navigation control than\nother methods in unknown environment.
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