CMD-SLAM: A Fast Low-bandwidth Centralized Multi-robot Direct Stereo SLAM

In this paper, we propose a centralized multi-robot stereo SLAM method based on a direct approach, with the aim of achieving Fast, Low-bandwidth, and Semi-dense mapping for collaborative applications, namely CMD-SLAM. In CMD-SLAM, each agent independently runs stereo-DSO as a front-end visual odometry(VO) and shares information with the central server via the TCP/IP protocol. To lower the bandwidth, we have designed a new communication strategy. Additionally, we employ a LiDAR descriptor-based place recognition method in the server’s back-end. This method fully exploits the information from the 3D point cloud structure generated during the direct method odometry, achieving efficient loop closure detection. In optimization, to achieve a balance between accuracy and speed, we adopt a Sim(3) pose graph optimization (PGO) and employ some trick to reduce the time consumption. Finally, we evaluate CMD-SLAM on publicly available datasets and large-scale outdoor environments, comparing it with state-of-the-art approaches to demonstrate its effectiveness.