The Digital, Industry and Space sector is a living ecosystem in Europe, where Horizon Europe projects do not work in silos but aim to learn from each other and create synergies that will take their impact to a higher level.
AID4SME is privileged to have been funded alongside five other projects: ROB4GREEN, iBot4CRMs, COSMIC, AEROSUB, and AMALTEA. Together, these projects form a cluster that will focus on creating synergies in exploitation, dissemination, and communication activities, the exchange of knowledge, and overcoming common challenges.
To maximise the visibility of these projects, AID4SME has been working on getting to know them better. As a result, AEROSUB project coordinator, Andry Maykol Pinto, has kindly agreed to an interview to present his project, share how autonomous multi-domain robotic fleets are transforming offshore wind operations, discuss the extreme challenges of marine infrastructure maintenance, and highlight common opportunities for both AEROSUB and AID4SME (and how they can cooperate). Don’t miss this insightful piece!
Coordinator profile
Andry Maykol Pinto concluded the Doctoral Program in Electrical and Computer Engineering with thesis related to Robotics, from the Faculty of Engineering of the University of Porto, in 2014. At the same institution, he obtained a Master in Engineering Electrotechnical and Computers in 2010. Currently, he works as a Area Manager for Inspection and Maintenance at the Center for Power and Energy Systems at INESC TEC and as an Associate Professor at the Faculty of Engineering of the University of Porto.
Could you explain the AEROSUB project in a nutshell?
AEROSUB (Automated Inspection Robots for Surface, Aerial and Underwater Substructures) is a European research project that develops fully unmanned robotic solutions for inspecting and maintaining offshore wind farms without requiring human presence on site. The project deploys an orchestrated fleet of robots: an Uncrewed Fleet Carrier (UFC) acting as a mothership, Unmanned Surface Vehicles (USVs), Remotely Operated Vehicles (ROVs), Unmanned Aerial Vehicles (UAVs), and long-endurance drones (UAS). These are powered by AI, digital twin technology, and data analytics to perform monitoring, inspection, cleaning, and light maintenance across aerial, surface, and underwater domains, in BVLOS (Beyond Visual Line of Sight) conditions.
The project targets TRL 6-7 and will be validated at two real demonstrators in Portugal: the ATLANTIS Test Centre (coastal testbed) and the WindFloat Atlantic commercial offshore wind farm. The 48-month project brings together 16 partners across 6 countries, coordinated by INESC TEC, with a total budget of approximately €12 million and EU contribution of €10 million.
Key headline ambitions include reducing CO₂ emissions from O&M by up to 15 million tonnes, cutting O&M costs by €2,400/MW/year, lowering the levelized cost of electricity (LCOE) by 2.5%, and achieving zero fatalities/injuries in O&M by 2030.
What makes underwater and aerial robotic inspection so challenging in offshore wind environments compared to traditional onshore infrastructure maintenance?
Several compounding factors make this uniquely difficult:
Environmental harshness. Traditional onshore infrastructure is accessible in almost any weather. Offshore wind farms are exposed to wave heights above 4m and wind speeds higher than 10 m/s. These harsh conditions affect multiple robot platforms (UAVs, ROVs, USVs) that must operate reliably together.
GPS and sensor degradation. Operating near large metallic offshore structures causes GPS signal interference and IMU disruption from local electromagnetic fields, making precise positioning and navigation far harder than onshore. Underwater, GPS is not an option at all, forcing reliance on acoustic positioning systems prone to drift errors.
Underwater visibility. Sub-sea environments suffer from colour distortion, contrast loss, marine snow and high turbidity, severely degrading the 2D/3D perception that robots need for accurate inspection. These conditions simply don’t affect onshore inspection.
Communication constraints. Underwater and remote offshore operations face high-latency and intermittent communications, making real-time control unreliable. The UAV, for instance, requires semi-autonomous features because continuous high-bandwidth links over many kilometres are impractical.
Multi-domain coordination. Unlike onshore inspection (typically a single team/vehicle), offshore IMR requires simultaneous coordination of aerial, surface and underwater robots in dynamic conditions, with each robot’s motion affected by waves and wind while they interact with moving floating structures.
Regulatory immaturity. BVLOS operations, floating structure standards and certification frameworks for unmanned offshore robotics are still being developed. There is no settled regulatory equivalent to the mature onshore infrastructure maintenance ecosystem.
How does translating real-time robotic inspection data into actionable maintenance insights help reduce the overall cost of electricity (LCOE) for renewable energy?
Reducing downtime. AI-powered defect detection automatically identifies blade cracks, corrosion, biofouling and coating damage across aerial and underwater components, cutting the time operators need to assess inspection data by over 50% and reducing human error by ~35%. Faster and easier anomaly detection means improved intervention planning in earlier stages of damage, reducing the overall turbine downtime by up to 60%.
Shifting from reactive to predictive maintenance. The digital twin framework integrates real-time sensor data, metocean conditions and historical inspection records to generate life prognostic estimates and prioritised maintenance recommendations. This enables opportunistic rather than corrective maintenance, avoiding expensive emergency deployments in undesirable weather and sea-state conditions.
Increasing accessible weather windows. By removing humans from the operational loop, AEROSUB pushes weather operational limits to 2m wave height and 13 m/s wind speed, increasing available inspection days from 634 to over 1,051 per year. More inspection windows mean defects are caught earlier, before they escalate into costly structural failures.
Eliminating vessel costs. Traditional O&M uses Crew Transfer Vessels and Service Operation Vessels, which account for over 80% of offshore O&M costs. Replacing these with the unmanned UFC and its robotic fleet eliminates crew transport, accommodation, and large vessel fuel costs, directly reducing per-MWh operating expenditure.
Aggregate LCOE impact. Estimates cost savings of €2,400/MW/year and a 2.5% reduction in LCOE, with autonomous subsea survey systems reducing I&M costs by an estimated €2,785/MW/year.
What are the potential opportunities and touchpoints between AEROSUB and AID4SME?
AEROSUB offers several natural touchpoints with AID4SME, particularly through its strong focus on SME participation, technology transfer and workforce development. SMEs can benefit from licensing key exploitable results (e.g., AI-based perception, BVLOS flight control and aerial manipulation technologies), access the ATLANTIS Test Centre to validate and de-risk innovative solutions, and adopt the AI-as-a-Service platform for automated defect detection in inspection activities. In addition, AEROSUB’s reskilling and upskilling programmes provide valuable opportunities to strengthen SME capabilities in AI, robotics, and data-driven operations, while the project’s growing offshore O&M ecosystem creates new supply chain, subcontracting, and innovation opportunities for SMEs developing sensors, software, UAV technologies, and inspection services.