Adaptive Sampling Using Swarms of Smart Autonomous Underwater Vehicles

The goal here is to mount sensors on large numbers – “swarms” – of autonomous underwater ìsmartî vehicles and deploy the vehicles for optimal results. At this time operators are not sure how to accomplish this due to the many variables in sensor performance and the constant changes in the dynamics of the ocean field. Adaptive sampling techniques will be developed using physical-biogeochemical ocean dynamics and modeling; dynamical system theory; uncertainty prediction; decision-making under uncertainty; artificial intelligence; bio-inspired behaviors and algorithms with emergence of global properties; and distributed computing. Future applications include: assessing the impact of “green” ocean energy industries; ecosystem-based management of fisheries; pollution monitoring; homeland security and harbor protection; efficient ocean exploration; and multi-scale climate monitoring and prediction.