This case study involves heterogeneous marine vehicles (surface and underwater vehicles such as autonomous crafts, AUVs or underwater gliders) to achieve a scientific mission composed of several phases (exploration and survey, scientific sensor data sampling). Fleets of autonomous vehicles can optimize the operational mission time (several vehicles will perform faster the same mission than one) as well as to achieve mission goals that could not be accomplished with a single vehicle. A coordinated underwater inspection mission will require sharing of data (scientific payload data, or vehicle data) collected by the different vehicles resulting in a “sensing network” when the fleet seen as a global system.

The particular challenges investigated in FeedNetback include:

Architecture: the need to coordinate the actions of the vehicles over channels with limited capacity.

• Control & Complexity: Centralised vs decentralized control strategies, which are at the heart of this application.

• Control & Communication: The available bandwidth is severely limited (few bits per second), communication is subject to long and variable propagation delays, multi-path, fading and high bit error rates.

• Control & Computation: The case study will make use of the adaptive sampling strategies, and distributed collaborative computation.

• Control and Energy: In this application battery power is limited and usually batteries cannot generally be recharged. Energy resources must be shared between between functions