Real-time Bandwidth-efficient Occupancy Grid Map Synchronization for Multi-Robot Systems

Robot swarms are increasingly being applied in various domains. However, due to the inherent limitation imposed by low real-time communication bandwidth, the synchronization of environmental information among multiple robots remains a persistent and challenging problem in practical applications. In response to this challenge, we introduce a comprehensive framework for synchronizing occupancy grid maps (OGMs) in practical multi-robot systems that operate under communication bandwidth constraints. In our research, we elaborately design the data structure of transmitted local OGMs and employ the Hilbert space-filling curve for voxel sorting. By adopting this approach, data redundancy is effectively increased, resulting in lower information entropy for compression and significantly reducing the volume of communication data. Finally, our framework outperforms the benchmark method by reducing the average and maximum bandwidth usage by more than 10 times in high-resolution scenarios. Moreover, our method has been successfully applied in the multi-UAV autonomous navigation application, demonstrating its real-time and bandwidth-efficient nature, as well as its practical value.