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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). pp. 47-56. ISSN 1859-387X

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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
Divisions: Faculty of Information Technology (FIT)
Depositing User: Lê Vũ Hà
Date Deposited: 23 Nov 2017 07:10
Last Modified: 23 Nov 2017 07:10
URI: http://eprints.uet.vnu.edu.vn/eprints/id/eprint/2666

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