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Autonomous smart robot for path predicting and finding in maze based on fuzzy and neuro‐Fuzzy approaches
Author(s) -
Batti Habiba,
Ben Jabeur Chiraz,
Seddik Hassene
Publication year - 2021
Publication title -
asian journal of control
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.769
H-Index - 53
eISSN - 1934-6093
pISSN - 1561-8625
DOI - 10.1002/asjc.2345
Subject(s) - adaptive neuro fuzzy inference system , fuzzy logic , mobile robot , controller (irrigation) , matlab , computer science , robot , control engineering , holonomic , artificial intelligence , fuzzy control system , neuro fuzzy , control theory (sociology) , engineering , control (management) , agronomy , biology , operating system
The navigation of autonomous mobile robots has in recent times gained interest from many researchers in different areas such as the industrial, agricultural, and military sectors. This paper aims at carefully investigating two advanced types of approaches for guiding a non‐holonomic mobile robot to navigate in an environment area cluttered with static obstacles. Firstly, a Fuzzy logic controller (FLC) was designed, using trapezoidal shape Membership functions (MF's). Secondly, an Adaptive neuro fuzzy inference system (ANFIS) controller was used to optimize the results obtained from trapezoidal fuzzy controller. To validate the feasibility and effectiveness of the proposed models, V‐REP and MATLAB software are used. A comparative evaluation is, then, done on the basis of speed. The simulations results showed that the mobile robot could navigate successfully into maze environment with both proposed approaches but ANFIS controller provided better results in comparison to fuzzy controller.