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AUV Adaptive Sampling Methods: A Review

期刊

APPLIED SCIENCES-BASEL
卷 9, 期 15, 页码 -

出版社

MDPI
DOI: 10.3390/app9153145

关键词

autonomous underwater vehicle(s); maritime robotics; adaptive sampling; underwater feature tracking; in-situ sensors; sensor fusion

资金

  1. Australian Research Council's Special Research Initiative under the Antarctic Gateway Partnership [SR140300001]
  2. Fisheries and Oceans Canada through the Multi-partner Oil Spill Research Initiative (MPRI) 1.03: Oil Spill Reconnaissance and Delineation through Robotic Autonomous Underwater Vehicle Technology in Open and Iced Waters
  3. Australian Government Research Training Program Scholarship

向作者/读者索取更多资源

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.

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