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Autonomous Acoustic Ground Discrimination System for Seagrass Characterisation

用于海草表征的自主声学地面识别系统

基本信息

批准号：
10004706
负责人：
金额：
$ 25.92万
依托单位：
HYDROSURV UNMANNED SURVEY (UK) LTD
依托单位国家：
英国
项目类别：
Collaborative R&D
财政年份：
2021
资助国家：
英国
起止时间：
2021 至无数据
项目状态：
已结题

来源：
https://gtr.ukri.org/projects?ref=10004706
关键词：
Autonomous Acoustic Ground Discrimination System

项目摘要

HydroSurv Unmanned Survey (UK) Ltd, (_HydroSurv_), an early-stage impact-focused designer, builder and operator of Uncrewed Surface Vehicles (USVs) is collaborating with the University of Plymouth to develop a new tightly-integrated robotic survey platform that features a new Acoustic Ground Discrimination System (AGDS) to put a transformative non-invasive, low-impact and economic monitoring solution for seagrass meadows in the hands of conservation bodies.Building upon the existing research performed by University of Plymouth, the project will develop an end-to-end solution from the sensor and embedded vehicle components to a cloud-based data-hosting solution optimised for seagrass mapping, providing an economic change comparison modelling between resurveys. The processing solution will involve developing and training new machine-learning algorithms to classify submerged aquatic vegetation.The project provides more than 43 days of on-water validation and testing, including technology demonstrations for review by key stakeholders Natural England (solution tester), South West Lakes Trust and the National Oceanography Centre.The solution is developed to provide a new technology and a new capability to respond to future needs to protect and restore our seagrass habitats around the globe, driving benefits such as blue carbon sequestration, protection of marine biodiversity and creating the conditions for security of fisheries and ocean food sources.

HydroSurv Unmanned Survey（UK）Ltd，（_HydroSurv_）是一家专注于无人水面车辆（USV）早期冲击的设计师、建造商和运营商，目前正在与普利茅斯大学合作开发一种新的紧密集成的机器人勘测平台，该平台具有新的声学地面识别系统（AGDS），低影响和经济监测解决方案的海草草甸在手中的保护机构。建立在现有的研究进行普利茅斯大学，该项目将开发一个端到端解决方案，从传感器和嵌入式车辆组件到基于云的数据托管解决方案，为海草测绘进行优化，提供了一个重新调查之间的经济变化比较模型。该处理解决方案将涉及开发和训练新的机器学习算法，以分类沉水水生植被。该项目提供超过43天的水上验证和测试，包括技术演示，供主要利益相关者Natural England审查。（溶液测试仪），该解决方案的开发旨在提供一种新的技术和新的能力，未来需要保护和恢复我们在地球仪周围的海草生境，推动蓝碳固存、保护海洋生物多样性以及为渔业和海洋食物来源的安全创造条件等惠益。