Multi-sensor fusion localization algorithm for outdoor mobile robot

Abstract

Abstract In this paper, the multi-sensor fusion positioning technology of outdoor mobile robot is studied, and a real-time outdoor positioning algorithm combining GPS and lidar odometry is proposed. Lidar odometry based on 3D lidar for point cloud feature matching is realized. At the same time, a covariance matrix reflecting the local positioning information of the lidar odometry is constructed in real time according to the matching distance and the absolute median difference, and the accuracy factor, the circular probability error, etc. are used as the standard GPS. The positioning effect is evaluated to measure the respective positioning effects of the lidar odometry and GPS. On this basis, the GPS is used as the global factor in the pose structure, and the lidar odometry is used as the local factor to construct the pose observation constraint, and the global nonlinear trajectory optimization is carried out to realize the outdoor real-time positioning of the mobile robot. Experimental results and data analysis verify the effectiveness and practicability of the proposed method.