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: 2022
• 资助国家: 加拿大
• 起止时间: 2022-01-01 至 2023-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=752777
• 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环境问题，具有严重的不利环境和社会经济影响。漏油是污染的一种形式；海洋中的进一步化学径流和塑料是其他的。我们的生态系统的气候变化和严重降解是这种污染的一些结果。风险增加，墨西哥湾的深水地平线井喷，毛里求斯的MV Wakashio在2018年和2019年溢出了纽芬兰，这扩大了对溢油溢油对抗的潜在需求与当前反应能力的差距。水柱中有关石油和其他污染的信息对于理解地下羽流行为至关重要，这反过来又可以及时有效缓解。在墨西哥湾爆破之后，自动驾驶水下车辆（AUV）哨兵被成功地用于表征被困在约1200 m深度的淹没油，并对受影响区域进行了全面的分析。在这项研究中，AUV能力将专门用于理解海洋污染和反应：首先，一种创新的自适应任务计划方法，用于不连续的斑块羽毛，由非溶质油滴云或其他潜在潜在的物品（例如微型塑料）组成，将被研究以提高AUV及其在板上的Sensors in plelineating plelumeser的表面上的表现。使用自适应采样，AUV根据板载传感器检测到的李子的特征，自主对其任务路径进行实时修改。因此，AUV路径集中在感兴趣的区域和传感器确定的信息丰富的区域中，从而优化了AUV响应。其次，将与加拿大AUV制造商一起研究远程AUV能力，以使大量的高耐用海洋污染监测任务完成，以便旨在设置监视人员和导致缓解测量的警报。将合并在水面上的可再生能源电池，以及自动导航和避免碰撞系统，与为自动运输开发的电池相似，以促进这些新设计的AUV设计，以在海面环境中长期安全地运行。第三，将研究对监测海洋污染所需的这些远程远距离操作的分析，并将开发新的方法，以确保向其他海洋使用者（例如人，船只和船只）以及通过水下噪声和潜在污染的潜在污染的环境的AUV部署风险。这是必不可少的组成部分，因为越来越多的自动驾驶汽车填充了海面。这项研究的目标社区包括监管机构，海洋污染机构，溢油响应组织，海上石油行业，AUV制造商，运营商和海洋学家。