Automated Robotic Ocean Biodiversity Observation Glider (AROBOG)

Seaweed Generation正在开发一种远程操作的自动水下机器人，该机器人能够使用高光谱相机和被动声学记录进行生物多样性监测。机器学习将用于开发动物识别和物种识别的方法。我们的AUV滑翔机（基于先前开发的设计）由电动推进器提供动力，使其能够遵循详细的“飞行”计划。太阳能光伏对接站为滑翔机提供充电点以及传输收集到的数据的点。作为监测和观察海藻农场和离岸风电场对生物多样性的潜在影响的新颖设计，该项目将集中于创建远程操作的观测阵列，利用机器学习来处理数据，以与记录的物种进行“匹配”，以及我们的滑翔机能够“解开”并返回其对接/充电站。我们将通过机器学习软件和开源数据集来运行观测阵列收集的数据，以使物种识别和量化更容易和更快。我们的项目旨在使长期的海洋生物多样性监测在具有挑战性的偏远沿海和近海环境中更容易获得，更具成本效益。

Seaweed Generation are developing a remotely operated automated underwater vehicle that is able to carry out biodiversity monitoring using hyperspectral cameras and passive acoustic recording.Machine learning will be used to develop methods for animal recognition and species identification.Our AUV glider (based on a previously developed design) is powered by electric thrusters giving it the ability to follow detailed "flight" plans.A solar PV docking station provides a charging point for the glider as well as a point for transmitting the collected data.As a novel design to monitor and observe potential impacts to biodiversity on seaweed farms and off-shore windfarms, this project will focus on the creation of the remotely operated observation array, processing of data using machine learning to 'match' against recorded species, and the capacity of our glider to 'untether' and return to its docking / charging station.We will be running the data collected by the observation array through machine learning software and open source datasets to make species identification and quantification easier and faster. Our project aims to make long term marine biodiversity monitoring more accessible and cost effective in the challenging remote coastal and off-shore environment.