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Automated Inspection Robots for Surface, Aerial and Underwater Substructures

Project description

Robots for renewable energy structures’ automated inspection

Robots are increasingly used across various fields, and the renewable energy sector’s need for sustainability could benefit from robotic solutions in floating offshore wind farms. The EU-funded AEROSUB project will develop advanced robotic solutions for both fixed and floating offshore wind farms, focusing on improving operation and maintenance procedures to enhance the sustainability of renewable energy in challenging environments. The project will demonstrate how robotics, integrated with AI and data analytics, can reduce CO2 emissions from operations by up to 15 million tonnes and lower the levelised cost of electricity by 2.5 %. It will use various robotic platforms to optimise collaboration between humans and robots, minimising personnel exposure to hazardous environments.

Objective

AEROSUB will develop world-class robotic solutions for different wind energy operating scenarios – fixed and floating offshore wind farms, promoting innovations for operation and maintenance (O&M) procedures to foster the competitiveness and sustainability of renewable energy production in challenging environments. AEROSUB will demonstrate the added value of robotics deeply integrated with advanced AI and data analytics technologies and their potential of reducing the eCO2 emissions of O&M operations by up to 15M tonnes, enabling cost savings by 2,400€/MW/year and lowering the levelized cost of electricity (LCOE) of offshore wind energy by 2.5%. By deploying an orchestration of multiple robotic platforms, including Uncrewed Fleet Carrier (UFC), Unmanned Surface Vehicle (USV), Remotely Operated Vehicles (ROVs), long endurance aerial drones (UAS), and Unmanned Aerial Vehicles (UAVs), and optimizing human-robot and robot-robot collaboration, AEROSUB aims to reduce the on-site humans’ exposure to dangerous and strenuous environments.
Large scale pilots related to monitoring, inspection, cleaning, and maintenance of structures below and above water line will be performed autonomously by AEROSUB solutions, which requires introducing AI-based features for enhancing perception and on-platform decision-making capabilities, improving collaborative navigation, manipulation, and mission planning. AEROSUB is proposing the first fully unmanned robotic solution for both aerial and underwater inspection and intervention, demonstrated in real offshore wind farm, to show an increased O&M operational efficiency of 40%, reducing of the associated downtime by 60% as well as the risk exposure of workers by 90%. Digital twin (DT) and AI solutions for automated information analysis of operational data, collected by remote robotic platforms in >30 operations, will increase the reactivity, responsiveness and intelligibility of the O&M operations: reducing the human burden by 80% to monitor

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Keywords

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Programme(s)

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Topic(s)

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Funding Scheme

Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.

HORIZON-IA - HORIZON Innovation Actions

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Call for proposal

Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.

(opens in new window) HORIZON-CL4-2024-DIGITAL-EMERGING-01

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Coordinator

INESC TEC - INSTITUTO DE ENGENHARIADE SISTEMAS E COMPUTADORES, TECNOLOGIA E CIENCIA
Net EU contribution

Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.

€ 1 589 755,00
Total cost

The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.

€ 1 589 755,00

Participants (13)

Partners (1)

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