A Multi-UAV Collaborative SLAM Method Oriented to Data Sharing

Built on the joint perception of multi-UAVs, collaborative Simultaneous Localization And Mapping (SLAM) can construct an incremental global environment map by means of the interaction and fusion of local maps, which can improve the accuracy, real-time and robustness of multi-UAV task coordination. Aiming at the problem of efficient data sharing and utilization, and the demand of fast, accurate and large scale area in cooperative SLAM of multi-UAVs, this paper proposes a novel centralized architecture based multi-UAV collaborative SLAM method-DSM-SLAM(Data Sharing Oriented Multi-UAV Collaborative SLAM), to achieve the efficient share and fusion. DSM-SLAM innovatively proposes: (1) a two-step relocation mechanism based on local map sharing, which achieves efficiently loop closure detection for the global map among multi-UAVs; (2) a map-fusion selection mechanism based on hierarchical clustering, which improves the speed and accuracy of map fusion. The proposed method can not only enhance the robustness performance of single UAV tracking and localization, but also can promote the collaborative processing capability of the multi-UAV visual SLAM system. We implement our DSM-SLAM system based on the Robot Operating System (ROS) and perform the experimental evaluation based on the public KITTI dataset. The experimental results demonstrate that the proposed DSM-SLAM can achieve relocalization of single UAV quickly and efficiently, and enhance the integrity and accuracy of global map construction by the adaptive selection of data fusion. © 2021, Science Press. All right reserved.