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The basic requirement of mobile robot localization is to know the information about its position and direction. The extended Kalman filter is an excellent tool to estimate the robot's posture in its work environment. Traditional extended Kalman filter uses fixed error covariance matrices Q and R, which does not conform the real situation. In this paper, GA-fuzzy logic controller is developed to adjust...
This paper studies the localization of a mobile robot based on neural network based extended Kalman filter (NNEKF) algorithm. Extended Kalman filter (EKF) is used to fuse the information acquired from both the robot optical encoders and ultrasonic sensors in order to estimate the current robot position and orientation. Then the error covariance of the EKF is tracked by the covariance matching technique...
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