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
Full text not available from this repository.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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