Using ultrasonic and vision sensors within extended kalman filter for robot navigation

Abstract

The simultaneous localization and map-building (SLAM) problem of robots with Extended Kalman Filter (EKF) framework were studied. Two types of sensing systems, ultrasound and computer vision, were mounted on the robot to perceive the environment so as to simultaneously localize the robot. The Kalman Filter (KF) is a linear, discrete-time, finite dimensional system with recursive structure that makes a digital computer well suited for its implementation. EKF provides a real-time solution to the navigation problem and to on-going estimation of the uncertainty acquired from vehicle motion and landmark observation.