TY  - INPR
ID  - SisLab2844
UR  - http://www.rev-jec.org
IS  - 1-2
A1  - Nguyen, Thi Thanh Van
A1  - Le, Vu Ha
A1  - Tran, Quang Vinh
Y1  - 2017///
N2  - 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.
PB  - REV
JF  - REV Journal on Electronics and Communications
VL  - 7
SN  - 1859-387X
TI  - A Robust Mobile Robot Navigation System using Neuro-Fuzzy Kalman Filtering and Optimal Fusion of Behavior-based Fuzzy Controllers
AV  - none
ER  -