LAUSR

Searching within an unknown environment quickly by utilising a small number of high-capacity robots or a large number of low-cost robots poses an endless question with a non-trivial answer. If the robot's operating environment is underwater, the problem becomes even more complicated due to its three-dimensional nature and the communication restrictions. In this paper, we propose an algorithm appropriate for target searching in unknown underwater environments. The proposed method considers a homogeneous decentralised multi-robot coordination scheme applied from a single-robot configuration to a large swarm. In this model, simple agents (SA) form smart swarms (SS), despite SA do not need to have a strong ability to transmit search and location information, and the SS can efficiently perform search tasks in unknown environments. Specifically, when a swarm performs a search task, agents only search according to the simple strategy and share mapping information within their communication range, enhancing search efficiency. Simulation results demonstrate the effectiveness and that search time reduces proportionally by increasing the number of robots comprising the swarm, while the repetition search rate does not increase with the expansion of the swarm size. We believe that our SS architecture provides insights into the future application of swarm intelligence.