Hybrid Coordination Strategy of a Group of Cooperating Autonomous Underwater Vehicles
Résumé
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
preliminary results of the hybrid coordination strategy applied on a fleet of 3 AUVs