CCMD-SLAM: Communication-Efficient Centralized Multirobot Dense SLAM With Real-Time Point Cloud Maintenance

This article presents a communication-efficient centralized multirobot dense simultaneous localization and mapping (CCMD-SLAM) system with real-time point cloud maintenance, to address the limitations of data transmission and real-time creation and updating of dense maps in multirobot SLAM. This method solves the problem of high bandwidth consumption for information transmission in multirobot SLAM by preprocessing and compressing the transmitted data and filtering the red green blue-depth (RGB-D) information using the co-viewing degree of keyframes. The proposed method uses loop closure detection to integrate information from multiple robots and establish a global point cloud. In addition, a keyframe and point cloud storage mechanism is designed to facilitate real-time maintenance of global point cloud data. Through comprehensive evaluations using standard datasets and real-world experiments, CCMD-SLAM significantly alleviates data transmission pressures, enables flexible global point cloud management across multiple robots, and effectively achieves dense mapping for multirobot systems.