Position and Pose Estimation of Mobile Robots Based on Multisensor Information Fusion

• 1、Faculty of Information Technology , Beijing University of Technology, Beijing

Abstract：Position and pose estimation of a mobile robot is an important prerequisite for autonomous navigation of mobile robot pose estimation of the traditional inertial navigation of mobile robot. The position and pose estimation of traditional position estimation of inertial navigation requires the initial state of a given mobile robot, and the accumulated error is generated in the estimation process. Beacon-based localization has low positioning accuracy and difficult to provide reliable information for mobile robot yaw angle, based on those problems, this paper presents a fusion of Ultra Wide Band (UWB), gyroscope and encoder of multi-sensor information fusion algorithm to solve the defects of a single positioning method. UWB calculates the distance between the tag and the base station by Time of Flight(TOF) measurements, the position of the tag is calculated by the three orientation method, and the yaw angle velocity and line velocity of the mobile robot can be calculated by using a gyroscope and an encoder. On this basis, to derive the system state equation and observation equation, using the Extended Kalman Filter (EKF) to complete the multi sensor information fusion filtering, to improve the estimation of position and yaw angle of the mobile robot. The experiment shows that this algorithm can not only suppress the cumulative robotic sensor error, and can improve the precision of UWB, the mobile robot to obtain higher positioning accuracy and reliability of the yaw angle.

Keywords： mobile robot Position and pose estimation；Extended Kalman Filter；UWB multi sensor information fusion