SLAM integrated mobile mapping system in complex urban environments

In this paper, a SLAM-integrated MMS with the capability of efficient, consistent and robust mapping in complex environments where GNSS signal is intermittently lost is presented. The system is developed to take the feedback from mapping module to the localization module into account, which significantly improves the smoothness of the 6 DOF trajectory estimation. In particular, the complex mapping problem is modeled as a hierarchical factor graph to improve the computation efficiency of the optimization back-end. Moreover, GNSS signal is modeled as a plug-and-play constrained factor to facilitate the mapping process in complex urban environments. We evaluate the performance of the proposed method on KITTI benchmark, and compare the result with both the GNNS/INS system and SuMa, which represents the traditional MMS and the typical laser SLAM system respectively. The results confirm that the proposed method enables normal and accurate mapping even when the inavailability of GNSS is up to 60%. It outperforms the traditional MMS in terms of map consistency with an increase of 24.7% on average MME, and outperforms laser SLAM in terms of the absolute accuracy with 5.9 times increase on average RMSE.