Localization of a Robot Using Particle Filter with Range and Bearing

Abstract

This paper reports a localization method based on particle filter with range and bearing information for fixed landmarks. The method consists of motion model which predicts pose of a robot, sensor model which evaluates the predicted pose, and resampling which modifies the evaluated pose. The proposed particle filter method utilizes bearing information as well as range information. The results of a simulation show trajectories for estimated robot location. Also, there is a result for comparison of performances using the proposed method and extended Kalman filter based method.nd resampling which modifies the evaluated pose. The proposed particle filter method utilizes bearing information as well as range information. The results of a simulation show trajectories for estimated robot location. Also, there is a result for comparison of performances using the proposed method and extended Kalman filter based method.