Localisation and Navigation of a robot on an offshore wind turbine blade using intelligent algorithms

使用智能算法对海上风力涡轮机叶片上的机器人进行定位和导航

• 批准号: 10033977
• 金额: $ 50.29万
• 依托单位: BLADEBUG LIMITED
• 依托单位国家: 英国
• 项目类别: Collaborative R&D
• 财政年份: 2022
• 资助国家: 英国
• 起止时间: 2022 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=10033977
• 关键词: Localisation; Navigation; robot; offshore; wind

BladeBUG, working with Imperial College London and the Offshore Renewable Energy Catapult, are seeking funding to develop and test an autonomous robot capable of carrying out inspection, maintenance and repair work on offshore wind turbines.While robots can greatly benefit society, their deployment outside the well-controlled environment of factories and labs remain a challenge. Indeed, engineers cannot foresee every situation that a robot will have to face because everysituation is different. One of the objectives of this proposal is to overcome this challenge by leveraging recent advances in Artificial Intelligence (Machine Learning) to enable robots to autonomously learn how to recover from unexpected situations, like mechanical damage and changes in the surface of a wind turbine blade.This project will cement the UK's market-leading position as the global leader in offshore wind by addressing a key missing element of the supply chain -- autonomous robotic inspection, maintenance and repair of offshore turbine blades. Furthermore, this innovation, to be manufactured in the North-East of England, will be attractive to a global market as nations seek to derive more of their energy from renewable sources.

BladeBUG与伦敦帝国理工学院（Imperial College伦敦）和海上可再生能源弹射器（Offshore Renewable Energy Catapult）合作，正在寻求资金，以开发和测试一种能够对海上风力涡轮机进行检查、维护和修理工作的自主机器人。尽管机器人可以极大地造福社会，但在工厂和实验室等控制良好的环境之外部署它们仍然是一个挑战。事实上，工程师无法预见机器人将不得不面对的每一种情况，因为每一种情况都是不同的。该提案的目标之一是通过利用人工智能的最新进展来克服这一挑战（机器学习）使机器人能够自主学习如何从意外情况中恢复，比如机械损伤和风力涡轮机叶片表面的变化。这个项目将巩固英国的市场-通过解决供应链中的关键缺失环节--海上涡轮机叶片的自动机器人检查、维护和维修，我们将继续保持海上风电领域全球领导者的领先地位。此外，这项将在英格兰东北部制造的创新将对全球市场具有吸引力，因为各国都在寻求从可再生能源中获得更多的能源。