Hybrid Coordination Strategy of a Group of Cooperating Autonomous Underwater Vehicles

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. Their small coverage can be significantly improved by using a fleet of coordinated underwater robots. This paper presents a strategy to coordinate a group of robots in order to systematically survey the seabed and detect small objects or singularities. The proposed hybrid coordination strategy is based on two main modes. The first mode relies on a swarm algorithm to organize the team in geometrical formation. In the second mode, the group formation is maintained using a hierarchical coordination. A finite state machine controls the high level hybrid strategy by defining the appropriate coordination mode according to the evolution of the mission. Before the sea validation, the behavior and the performance of the hybrid coordination strategy are first evaluated 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 using the Bullet solver and the estimated hydrodynamic coefficients. This paper presents and discusses the preliminary results of the hybrid coordination strategy applied on a fleet of 3 AUVs.