Extended Kalman Filtering (EKF) is proposed for: (i) the extraction of a fuzzy model from
numerical data; and (ii) the localization of an autonomous vehicle. In the first case, the EKF …

… The system is equipped with two sensors measuring cart position and rod angle,
respectively. These variables are used within a feedback loop to stabilize the system around the …

… cluster of sensors including a GPS receiver is usually used. Two other popular sensors are
… With these two sensors, the position of the vehicle is reckoned by applying basic kinematics’ …

… By fusing the data from multiple sensors, we can obtain an … extended Kalman filter node,
ekf_localization_node, for our robot_localization ROS package. Its support for multiple sensors …

… integration, and an ultrasonic sensor is employed to periodically … the multi-sensors are fused
using extended Kalman filter (EKF), in which the position measured by the ultrasonic sensor …

… missing measurements, the new measurement model (2) is capable of describing the actual
arrivals of the measured information from multiple sensors especially when only partial data …

… Due to complex environment and diversity of sensors, errors need … multiple sensors. We
then combine fuzzy sets with a novel trace optimization method based on extended Kalman filter …

… Two different distributed and centralized architectures are presented to integrate the multi-sensor
data based on extended Kalman filter … In this work, two different multi-sensor integration …

… localization by using multiple sensors fusion system based on Extended Kalman Filter. The
… Due to the laser sensor is sensitive to outdoor environments including moving objects and …

… Kalman filter. Probably the most widely used estimator for nonlinear systems is the extended
Kalman filter (… The EKF applies the Kalman filter to nonlinear systems by simply linearising …