Autonomous underwater vehicle sampling for hotspots in chlorophyll A (opens in a new tab)
Researchers developed an algorithm for autonomous underwater vehicles (AUVs) to efficiently map chlorophyll A hotspots by prioritizing sampling locations based on expected improvement. The system uses a Gaussian random field model to represent chlorophyll variations in space and time, updating in real-time with in-situ measurements. Field trials in Norway demonstrated the method’s adaptive sampling capabilities, comparing chlorophyll data with zooplankton distributions. Simulations showed the approach outperformed alternative sampling strategies.