Advancing Autonomous Underwater Vehicle Capability for Assessment of Marine Pollution

提高自主水下航行器评估海洋污染的能力

• 批准号: RGPIN-2021-02506
• 负责人: Bose, Neil
• 金额: $ 1.97万
• 依托单位: Memorial University of Newfoundland
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2021
• 资助国家: 加拿大
• 起止时间: 2021-01-01 至 2022-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=741806
• 关键词: Advancing; Autonomous; Underwater; Vehicle; Capability

Marine pollution is a global environmental problem that has severe adverse environmental and socio-economic impacts. Oil spills are one form of pollution; further chemical run-off and plastics in the ocean are others. Climate change and severe degradation of our ecosystem are some of the outcomes from this pollution. Increased risks, the Deepwater Horizon blowout in the Gulf of Mexico, the MV Wakashio in Mauritius, spills off Newfoundland in 2018 and 2019, have broadened the gap between the potential need for oil spill countermeasures and current response capabilities. Information about oil and other pollution in the water column is critical to understanding of subsurface plume behavior which in turn enables timely and effective mitigation. Following the Gulf of Mexico blowout, the autonomous underwater vehicle (AUV) Sentry was successfully used to characterize submerged oil that was trapped at a depth of approximately 1200 m and provided a comprehensive analysis of the impacted areas. In this research AUV capabilities will be advanced specifically for the understanding of marine pollution and response: Firstly, an innovative adaptive mission planning approach for discontinuous patchy plumes made up of non-soluble oil droplet clouds or other potential items of interest such as micro-plastics, will be researched to improve performance of AUVs and their onboard sensors in delineating subsurface plumes. Using adaptive sampling, the AUV autonomously modifies its mission path in real-time based on features of the plumes detected by on-board sensors. Hence the AUV path is concentrated within the areas of interest and in information-rich areas identified by the sensors, optimizing the AUV response. Secondly, long-range AUV capability will be researched in conjunction with Canadian AUV manufacturers to enable extensive high-endurance marine pollution monitoring tasks to be completed with the aim to put in place watchdog and alerts that lead to mitigation measures. Renewable-energy battery charging at the water surface coupled with autonomous navigation and collision avoidance systems, similarly to those being developed for autonomous shipping, will be incorporated to enable these new designs of AUVs to operate safely over long periods in the ocean surface environment.  Thirdly, risk-based analysis of these remote long range operations required for the monitoring of marine pollution will be researched and new methods will be developed to ensure that the risks of AUV deployment to other ocean users, such as people, ships and boats, as well as to the environment through underwater noise and the potential for pollution, are minimized. This is an essential component as an increasing number of autonomous vehicles populates the ocean surface.  The target community of this research includes regulators, marine pollution agencies, oil spill response organizations, the offshore petroleum industry, AUV manufacturers, operators and oceanographers.

海洋污染是一个全球性环境问题，对环境和社会经济造成严重的不利影响。石油泄漏是污染的一种形式;进一步的化学径流和海洋中的塑料是其他形式。气候变化和我们生态系统的严重退化是这种污染的一些后果。 风险增加，墨西哥湾的深水地平线井喷，毛里求斯的MV Wakashio，2018年和2019年纽芬兰岛的泄漏，扩大了溢油对策的潜在需求与当前响应能力之间的差距。关于水柱中的石油和其他污染物的信息对于了解地下羽流行为至关重要，这反过来又能够及时有效地减轻污染。在墨西哥湾井喷之后，自主水下航行器（AUV）哨兵成功地用于描述被困在大约1200米深处的水下石油，并对受影响地区进行了全面分析。 在这项研究中，AUV的能力将专门用于了解海洋污染和响应：首先，将研究一种创新的自适应使命规划方法，用于由不溶性油滴云或其他潜在的感兴趣的项目，如微塑料组成的不连续的片状羽流，以提高AUV及其机载传感器在描绘地下羽流方面的性能。利用自适应采样，AUV自主修改其使命路径实时的基础上的特征羽流检测到的板载传感器。因此，AUV路径集中在感兴趣的区域和传感器识别的信息丰富的区域内，优化AUV响应。 第二，将与加拿大自主式潜水器制造商一起研究远程自主式潜水器的能力，以便能够完成广泛的高耐久性海洋污染监测任务，目的是建立监督和警报，从而采取缓解措施。可再生能源电池在水面充电，再加上自主导航和防撞系统，类似于为自主航行开发的系统，将使这些新设计的水下机器人能够在海洋表面环境中长时间安全运行。风险--将对监测海洋污染所需的这些远程作业进行基于分析的研究，并将开发新的方法，确保将部署自主式潜水器对其他海洋使用者，如人、船舶和船只，以及通过水下噪音和潜在污染对环境造成的风险降到最低。随着越来越多的自动驾驶车辆进入海洋表面，这是一个必不可少的组成部分。这项研究的目标群体包括监管机构、海洋污染机构、溢油响应组织、海上石油工业、AUV制造商、运营商和海洋学家。