Global Localization of Mobile Robots Using Local Position Estimation in a Geo Tagged Wireless Node Sensor Network

Abstract

Precise localization of mobile robots in uncertain environments is a fundamental and crucial issue in robotics. In this paper, we propose an outdoor robot localization strategy using an extended Kalman filter (EKF). The method relies on the received signal strength (RSS) produced by wireless nodes, wheel odometry, and GPS to estimate a precise global position of the robot. The proposed method was evaluated using simulated experiments with different scenarios and sensors configurations. The results have shown the feasibility of the methodology.