Multi-AUV Cooperative Search Method Based on High-Capacity Chance Communication

Searching dynamic targets in unknown underwater environments is quite challenging for multiple autonomous underwater vehicles (AUVs) due to the limited stability of underwater communications. In this article, we propose a multi-AUV asynchronous update search strategy based on high-capacity chance communication to maximize target search performance under unstable communication condition. In this method, a real-time target situation awareness information map is established based on Bayesian theory. Each AUV can communicate opportunistically to share useful information and update its own information map individually, rather than having to update the information map in sync with other AUVs from moment to moment. AUVs’ local information map and raw sensing data are opportunistically exchanged via a high-capacity underwater wireless optical communication (UWOC) link and fused together. Then, based on the updated information map, the search route of each AUV is optimized through the predictive control approach. The effectiveness of the above method has been verified through Monte Carlo simulation. Results presented in this article suggest that the proposed method can achieve a comparable search performance against the global communication-based search with less requirement on communication stability.