Autonomous monitoring and prediction of marine pollution

海洋污染自主监测与预测

• 批准号: 1806216
• 金额: --
• 依托单位: University of Sheffield
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2016
• 资助国家: 英国
• 起止时间: 2016 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-1806216
• 关键词: Autonomous; monitoring; prediction; marine; pollution

The project 'Autonomous monitoring and prediction of marine pollution' is aiming to develop methods for autonomous mapping and monitoring of maritime spillages, usually oil slicks. This will enable long range mapping missions of multiple autonomous vehicles operating efficiently with minimal input from a human controller. High fidelity models of the sea and wind environment, the sensors and the unmanned vehicles will be developed for algorithm verification and testing, with a lower fidelity and real-time simulation to be used in the control loop. The industry sponsor, Andrew Moore and Associates, intends to utilise the research to gather information to support clean-up operations and legal claims that surround maritime accidents: Calculating the spillage epicentre and predicting future damages.

“海洋污染自主监测和预测”项目旨在开发自主测绘和监测海洋泄漏（通常是浮油）的方法。这将使多辆自动驾驶汽车的远程测绘任务能够在最少的人类控制器输入的情况下高效运行。海风环境、传感器和无人驾驶车辆的高保真度模型将用于算法验证和测试，控制回路将使用较低的保真度和实时仿真。该行业的发起人Andrew Moore and Associates打算利用这项研究来收集信息，以支持清理工作和围绕海上事故的法律索赔：计算泄漏震中和预测未来的损害。

项目成果

Optimal Model-Based Sensor Placement & Adaptive Monitoring Of An Oil Spill

• DOI: 10.1016/j.ifacol.2020.12.2010
• 发表时间: 2019-11
• 期刊: ArXiv
• 作者: Z. Hodgson;I. Esnaola;B. Jones