An Adaptive Sampling Solution using Autonomous Underwater Vehicles

Abstract

To achieve efficient and cost-effective sensing coverage of the vast under-sampled 3D aquatic volume, intelligent adaptive sampling strategies involving Autonomous Underwater Vehicles (AUVs) endowed with underwater wireless (acoustic) communication capabilities are essential. These AUVs should coordinate and steer through the region of interest, and cooperatively sense, preprocess and transmit measured data to onshore stations for processing and analysis. Given a scalar field to sample, i.e, a phenomenon like temperature or salinity distribution, the AUVs should coordinate to take measurements using minimal resources (time or energy) in order to reconstruct the field with admissible error. A novel adaptive sampling solution to minimize the sampling cost is proposed, which requires the AUVs to take a small number of samples from the field. We observe via simulations that our solution outperforms existing solutions that are based on Compressive Sensing (CS) techniques.