Neuro-Fuzzy Combination for Reactive Mobile Robot Navigation: A Survey

Brahim Hilali, Mohammed Ramdani, Abdelwahab Naji


Autonomous navigation of mobile robots is a fruitful research area because of the diversity of methods adopted by artificial intelligence. Recently, several works have generally surveyed the methods adopted to solve the path-planning problem of mobile robots. But in this paper, we focus on methods that combine neuro-fuzzy techniques to solve the reactive navigation problem of mobile robots in a previously unknown environment. Based on information sensed locally by an onboard system, these methods aim to design controllers capable of leading a robot to a target and avoiding obstacles encountered in a workspace. Thus, this study explores the neuro-fuzzy methods that have shown their effectiveness in reactive mobile robot navigation to analyze their architectures and discuss the algorithms and metaheuristics adopted in the learning phase.


Reactive navigation; Neuro-fuzzy combination; Mobile robot path planning; Fuzzy inference system; ANFIS; Metaheuristic


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