The Adaptive Sampling of Marine Robots in Ocean Observation: An Overview

Abstract

It is a costly and time-consuming practice to achieve ocean observation with sufficient spatial and temporal resolution. Luckily, it can be more efficient and effective by applying marine robots with adaptive sampling. The ocean environment and its uncertainties can be predicted during sampling to make planning of autonomous sensing for future operations of the marine robot. This article reviews various methods of adaptive sampling as well as robot path planning, weighing the benefits and drawbacks of each. In addition, three primary aspects of adaptive sampling are summarized: adaptive sampling architecture, multirobot sampling, and the dimensionality problem. The operation practice of adaptive sampling approaches in real applications is also investigated. Future trends for adaptive sampling of marine robots are also discussed to conclude several research directions that are not fully developed or remain unexplored, which will aid future studies.