AUV Adaptive Sampling Methods: A Review

• Published in: Applied sciences 2019-08, Vol.9 (15), p.3145
• Main Authors: Hwang, Jimin, Bose, Neil, Fan, Shuangshuang
• Format: Article
• Language: English
• Subjects: Adaptive sampling; Algal blooms; Automation; autonomous underwater vehicle(s); Autonomous underwater vehicles; Autonomy; Behavior; Eutrophication; in-situ sensors; maritime robotics; Oceans; Robotics; Robots; Sampling methods; sensor fusion; Sensors; underwater feature tracking; Vehicles; Vertical migrations; Water purification
• ISSN: 2076-3417; 2076-3417
• DOI: 10.3390/app9153145

Autonomous underwater vehicles (AUVs) are unmanned marine robots that have been used for a broad range of oceanographic missions. They are programmed to perform at various levels of autonomy, including autonomous behaviours and intelligent behaviours. Adaptive sampling is one class of intelligent behaviour that allows the vehicle to autonomously make decisions during a mission in response to environment changes and vehicle state changes. Having a closed-loop control architecture, an AUV can perceive the environment, interpret the data and take follow-up measures. Thus, the mission plan can be modified, sampling criteria can be adjusted, and target features can be traced. This paper presents an overview of existing adaptive sampling techniques. Included are adaptive mission uses and underlying methods for perception, interpretation and reaction to underwater phenomena in AUV operations. The potential for future research in adaptive missions is discussed.