Navigation of a Fuzzy-Controlled Wheeled Robot Through the Combination of Expert Knowledge and Data-Driven Multiobjective Evolutionary Learning

This article proposes a navigation scheme for a wheeled robot in unknown environments. The navigation scheme consists of obstacle boundary following (OBF), target seeking (TS), and vertex point seeking (VPS) behaviors and a behavior supervisor. The OBF behavior is achieved by a fuzzy controller (FC)...

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Vydané v:	IEEE transactions on cybernetics Ročník 52; číslo 8; s. 7388 - 7401
Hlavní autori:	Juang, Chia-Feng, Chou, Ching-Yu, Lin, Chin-Teng
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	United States IEEE 01.08.2022 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:	Ant colony optimization Barriers Behavior Coders Data-driven fuzzy systems evolutionary fuzzy control Fuzzy control Localization Localization method Mobile robots multiobjective optimization algorithms Multiple objective analysis Navigation Obstacle avoidance Optimization PD control Proportional integral derivative robot navigation Robot sensing systems Robots Task analysis Unknown environments
ISSN:	2168-2267, 2168-2275, 2168-2275
On-line prístup:	Získať plný text
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