Using an Adaptive Fuzzy Neural Network Based on a Multi-Strategy-Based Artificial Bee Colony for Mobile Robot Control

Cheng-Hung Chen, Shiou-Yun Jeng and Cheng-Jian Lin
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Cheng-Hung Chen: Department of Electrical Engineering, National Formosa University, Yunlin 632, Taiwan
Shiou-Yun Jeng: Department of Computer Science and Information Engineering, National Chin-Yi University of Technology, Taichung 411, Taiwan
Cheng-Jian Lin: Department of Computer Science and Information Engineering, National Chin-Yi University of Technology, Taichung 411, Taiwan

Mathematics, 2020, vol. 8, issue 8, 1-18

Abstract: This study proposes an adaptive fuzzy neural network (AFNN) based on a multi-strategy artificial bee colony (MSABC) algorithm for achieving an actual mobile robot navigation control. During the navigation control process, the AFNN inputs are the distance between the ultrasonic sensors and the angle between the mobile robot and the target, and the AFNN outputs are the robot’s left- and right-wheel speeds. A fitness function in reinforcement learning is defined to evaluate the navigation control performance of AFNN. The proposed MSABC algorithm improves the poor exploitation disadvantage in the traditional artificial bee colony (ABC) and adopts the mutation strategies of a differential evolution to balance exploration and exploitation. To escape in special environments, a manual wall-following fuzzy logic controller (WF-FLC) is designed. The experimental results show that the proposed MSABC method has improved the performance of average fitness, navigation time, and travel distance by 79.75%, 33.03%, and 10.74%, respectively, compared with the traditional ABC method. To prove the feasibility of the proposed controller, experiments were carried out on the actual PIONEER 3-DX mobile robot, and the proposed navigation control method was successfully completed.

Keywords: mobile robot control; reinforcement learning; fuzzy neural network; artificial bee colony algorithm; differential evolution (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2020
References: View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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