The efficient sharing of information is a commonly overlooked problem in methods proposed for cooperative multi-robot tasks. However, in multi-robot scenarios, especially when the communication network's quality of service is less than desirable, either in bandwidth or reliability, efficient information exchange is a key aspect for the successful deployment of coordinated robotic teams with proper exchange of information. Compression is a popular, well-studied solution for transmitting data

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... ugh constrained communications channels, and many general-purpose solutions are available as free and open-source software (FOSS) projects. There are various benchmarking tools capable of comparing the performance of these techniques, but none that differentiate between them in the compression of the typical data exchanged among robots in a cooperative task. Thus, choosing a compression technique to be used in this context is still a challenge. In this paper, the issue of efficiently communicating data among robots is addressed by comparing the performance of various compression techniques in a case study of multi-robot simultaneous localization and mapping (SLAM) scenarios using occupancy grids, a cooperative task usually requiring the exchange of large amounts of data.