High-Precision Localization Using Visual Landmarks Fused with Ranged Data

Abstract

Visual landmark matching with a pre-built landmark database is a popular technique for localization. Traditionally, landmark database was built with visual odometry system, and the 3D information of each visual landmark is reconstructed from video. Due to the drift of the visual odometry system, a global consistent landmark database is difficult to build, and the inaccuracy of each 3D landmark limits the performance of landmark matching. In this paper, we demonstrated that with the use of precise 3D Li-dar range data, we are able to build a global consistent database of high precision 3D visual landmarks, which improves the landmark matching accuracy dramatically. In order to further improve the accuracy and robustness, landmark matching is fused with a multi-stereo based visual odometry system to estimate the camera pose in two aspects. First, a local visual odometry trajectory based consistency check is performed to reject some bad landmark matchings or those with large errors, and then a kalman filtering is used to further smooth out some landmark matching errors. Finally, a disk-cache-mechanism is proposed to obtain the real-time performance when the size of the landmark grows for a large-scale area. A week-long real time live marine training experiments have demonstrated the high-precision and robustness of our proposed system.