Visual Localization of Inspection Robot Using Extended Kalman Filter and Aruco Markers

Abstract

This paper investigates a localization technology based on Aruco Markers for substation inspection robot. Extended Kalman Filter(EKF) algorithm is used to fuse odometer information and camera measurement data from detection of Aruco markers. The experiment results show that the localization problem can be solved by EKF localization based on Aruco markers efficiently. The localization algorithm can provide the inspection robot with relatively accurate position information and shield the impact of the dynamic environment.