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Inventions 2018, 3(1), 3; https://doi.org/10.3390/inventions3010003

Navigation of an Autonomous Wheeled Robot in Unknown Environments Based on Evolutionary Fuzzy Control

Department of Electrical Engineering, National Chung-Hsing University, Taichung 402, Taiwan
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Received: 21 November 2017 / Revised: 1 January 2018 / Accepted: 2 January 2018 / Published: 5 January 2018
(This article belongs to the Special Issue New Inventions in Vehicular Guidance and Control)
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Abstract

Navigation of a wheeled robot in unknown environments is proposed in this paper. The approach may be applied to navigating an autonomous vehicle in unknown environments, such as parking lots. The navigation consists of three parts: obstacle avoidance behavior, target seeking behavior, and a behavior supervisor. The obstacle avoidance behavior is achieved by controlling the robot to move along an obstacle boundary through evolutionary fuzzy control. In the evolutionary fuzzy control approach, a Pareto set of fuzzy controllers (FCs) is found though a multi-objective continuous ant colony optimization algorithm. Target seeking behavior is achieved by controlling the robot through hybrid proportional–integral–derivative (PID) controllers. The behavior supervisor determines the switching between obstacle avoidance and target seeking behaviors, where the dead-cycle problem is considered. Simulations and experiments were performed to verify the effectiveness of the proposed navigation scheme. View Full-Text
Keywords: navigation; target seeking; multi-objective optimization; fuzzy control; evolutionary robots; dead-cycle problem navigation; target seeking; multi-objective optimization; fuzzy control; evolutionary robots; dead-cycle problem
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).
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Chou, C.-Y.; Juang, C.-F. Navigation of an Autonomous Wheeled Robot in Unknown Environments Based on Evolutionary Fuzzy Control. Inventions 2018, 3, 3.

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