Monterey Bay Aquarium Research Institute, Moss Landing, CA, USA.
University of Hawai'i at Mānoa, Honolulu, HI, USA.
Sci Robot. 2021 Jan 13;6(50). doi: 10.1126/scirobotics.abb9138.
The deep chlorophyll maximum (DCM) layer is an ecologically important feature of the open ocean. The DCM cannot be observed using aerial or satellite remote sensing; thus, in situ observations are essential. Further, understanding the responses of microbes to the environmental processes driving their metabolism and interactions requires observing in a reference frame that moves with a plankton population drifting in ocean currents, i.e., Lagrangian. Here, we report the development and application of a system of coordinated robots for studying planktonic biological communities drifting within the ocean. The presented Lagrangian system uses three coordinated autonomous robotic platforms. The focal platform consists of an autonomous underwater vehicle (AUV) fitted with a robotic water sampler. This platform localizes and drifts within a DCM community, periodically acquiring samples while continuously monitoring the local environment. The second platform is an AUV equipped with environmental sensing and acoustic tracking capabilities. This platform characterizes environmental conditions by tracking the focal platform and vertically profiling in its vicinity. The third platform is an autonomous surface vehicle equipped with satellite communications and subsea acoustic tracking capabilities. While also acoustically tracking the focal platform, this vehicle serves as a communication relay that connects the subsea robot to human operators, thereby providing situational awareness and enabling intervention if needed. Deployed in the North Pacific Ocean within the core of a cyclonic eddy, this coordinated system autonomously captured fundamental characteristics of the in situ DCM microbial community in a manner not possible previously.
深海叶绿素最大值（DCM）层是开阔海洋的一个生态重要特征。DCM 无法通过航空或卫星遥感进行观测；因此，现场观测至关重要。此外，要了解微生物对驱动其新陈代谢和相互作用的环境过程的响应，需要在与随海流漂移的浮游生物种群一起移动的参考系中进行观测，即拉格朗日观测。在这里，我们报告了一种协调机器人系统的开发和应用，用于研究在海洋中漂流的浮游生物群落。所提出的拉格朗日系统使用三个协调的自主机器人平台。焦点平台由配备有机器人水样采集器的自主水下航行器（AUV）组成。该平台在 DCM 群落中定位并漂移，定期采集样本，同时持续监测当地环境。第二个平台是配备有环境感测和声学跟踪能力的 AUV。该平台通过跟踪焦点平台并在其附近进行垂直剖面来描述环境条件。第三个平台是配备有卫星通信和海底声学跟踪能力的自主水面车辆。该车辆在对焦点平台进行声学跟踪的同时，还充当通信中继，将海底机器人与人类操作员连接起来，从而提供态势感知，并在需要时进行干预。该协调系统在北太平洋的一个气旋性涡流核心中部署，以以前不可能的方式自主捕获了原位 DCM 微生物群落的基本特征。
