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A Robust Mobile Robot Navigation System using Neuro-Fuzzy Kalman Filtering and Optimal Fusion of Behavior-based Fuzzy Controllers

Nguyen, Thi Thanh Van and Le, Vu Ha and Tran, Quang Vinh (2017) A Robust Mobile Robot Navigation System using Neuro-Fuzzy Kalman Filtering and Optimal Fusion of Behavior-based Fuzzy Controllers. REV Journal on Electronics and Communications, 7 (1-2). ISSN 1859-387X (In Press)

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Abstract

This study proposes a control system model for mobile robots navigating in unknown environments. The proposed model includes a neuro-fuzzy Extended Kalman Filter for localization task and a behaviorbased fuzzy multi-controller navigation module. The neuro-fuzzy EKF, used for estimating the robot’s position from sensor readings, is an enhanced EKF whose noise covariance matrix is progressively adjusted by a fuzzy neural network. The navigation module features a series of independently-executed fuzzy controllers, each deals with a specific navigation sub-task, or behavior, and a multi-objective optimizer to coordinate all behaviors. The membership functions of all fuzzy controllers play the roles of objective functions for the optimizer, which produces an overall Pareto-optimal control signal to drive the robot. A number of simulations and real-world experiments were conducted to evaluate the performance of this model.

Item Type: Article
Subjects: Electronics and Communications > Electronics and Computer Engineering
Divisions: Faculty of Electronics and Telecommunications (FET)
Depositing User: Nguy�n Th
Date Deposited: 22 Dec 2017 23:40
Last Modified: 22 Dec 2017 23:40
URI: http://eprints.uet.vnu.edu.vn/eprints/id/eprint/2844

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