Hybrid coordination strategy for systematic and detailed optical acquisition of the seabed by a group of robots

In the underwater environment, the needs of data acquisition have significantly increased over the last decades. As electromagnetic waves show poor propagation in sea water, acoustical sensing is generally preferred. However, the emergence of small and low cost autonomous underwater vehicles (AUV) allow for rethinking the underwater use of optical sensors as their small coverage can be significantly improved by using a fleet of coordinated underwater robots. This paper presents a strategy to coordinate the group of robots in order to systematically survey the seabed to detect small objects or singularities. The proposed hybrid coordination strategy is defined by two main modes. The first mode relies on a swarm algorithm to organize the team in geometrical formation. In the second mode, the robot formation is maintained using a hierarchical coordination. A finite state machine controls the high level hybrid strategy by defining the appropriate coordination mode according the evolution of the mission. Before at sea validation, the behavior and the performance of the hybrid coordination strategy are first assessed in simulation. The control of individual robots relies on visual servoing, implemented with the OpenCV library, and the simulation tool is based on Blender software. The dynamics of the robots has been implemented in a realistic way in Blender by using the Bullet solver and the hydro-dynamic coeficcients estimated on the actual robot. This paper presents and discusses the first results of the hybrid coordination strategy applied on a fleet of 3 AUV's.