Research on service robots robust relocalization algorithm based on 2D/3D map of indoor environment

Abstract

An indoor service robot can establish a 3D map of the environment by a visual sensor. When the robot uses the established map again, there is a situation that the robot's view is in a new position and the relative position of the map can not be obtained. A relocalization algorithm based on multi-dimensional map information is proposed to solve the problem. Based on the established 3D environment map, the algorithm samples a 2D map and matches the map with the 2D observation information of the current frame based on the particle filter algorithm to obtain the robot's initial position. Then, the target point cloud corresponding to the current frame is segmented in the 3D map, and the exact pose relationship between the current frame cloud and the target point cloud is calculated by the iterative closest point algorithm. The SVD decomposition and g2o optimization are used in the method to improve the computational efficiency and accuracy. Finally, the relocalization experiments under the wide range of robot perspective are carried out in the indoor environment. The results verify the effectiveness and robustness of the algorithm.