Precise Localization of Mobile Robots via Odometry and Wireless Sensor Network

Precise localization of mobile robots in uncertain environments is a fundamental and crucial issue in robotics. In this paper, to deal with the unbounded accumulated errors of dead reckoning (DR)-based localization, wireless sensor network (WSN)-based localization is applied to calibrate the uncertainty of odometry using a Kalman filter (KF). In addition, to further aid in obtaining precise positions and reduce uncertainty, a novel backward dead reckoning (BDR) localization approach is proposed. The experimental results demonstrate the success and reliability of the proposed method.