Research on Autonomous Localization Method of Coal Mine Underground Mobile Robot Based on Multi sensor Fusion

Abstract

Aiming at the complex and relatively closed underground environment of coal mine where mobile robot work, this paper proposes an autonomous localization method for coal mine underground mobile robot based on multi-sensor fusion. A simple robot localization model based on turning is established, which replaces the traditional method of estimating complex ground parameters in coal mine tunnel. In order to improve locating accuracy, a multi-sensor fusion localization algorithm based on EKF+AMCL (Extended Kalman Filter+ Adaptive Monte Carlo Localization) is proposed. The EKF algorithm is used to eliminate the white Gaussian noise in the path angle signal of the robot. By the AMCL algorithm, the location and path angle of the robot is fused with Lidar and Map data to obtain real time location and path angle after corrected errors. The experiment shows that in the established robot turning tunnel environment, the high-precision autonomous localization of the robot can be achieved, with an average location error of 0.027m and an average path angle error of 2.23°.