ADBISOV | ESA Space Solutions

Objectives of the service

Offshore wind turbine blade inspection is a costly and logistically demanding process. Current methods rely on dedicated inspection vessels, so the cost per turbine is high and operators stretch intervals to two or three years.

ADBISOV addresses this challenge by integrating a vessel-based autonomous drone system directly onto Service Operation Vessels (SOVs). SOVs already access turbines routinely for maintenance, spending around 2x20 minutes at each turbine during technician transfers. ADBISOV uses these existing windows to capture blade inspection imagery autonomously, with a pilot or responsible person supervising on the vessel today, without requiring any additional vessel time or dedicated inspection campaigns.

AI-assisted cloud analytics process the captured imagery, with findings reviewed by blade experts before any repair decision is made, and deliver inspection reports within a 48-hour target via a secure web dashboard.

The project aims to demonstrate the technical and commercial viability of this approach, achieve a substantial reduction in inspection cost, and build the evidence base for moving from biennial to annual full-farm inspection where a drone is resident and available. The project is an 18-month ESA Business Applications Demonstration Project, conducted by Perceptual Robotics in partnership with ORE Catapult, with active participation from pilot industry partners.

Users and their needs

The service targets users in the United Kingdom and across European offshore wind markets. Three main user groups are involved:

Offshore Wind Farm Operators: Asset owners responsible for maximising energy production. They need lower-cost, higher-frequency blade inspections to reduce the risk of catastrophic blade failures, where one replacement can run to several hundred thousand euros, and leading edge erosion losses of close to 3% of annual energy output.
Service Operation Vessel Operators: Companies providing marine logistics platforms that service turbines at sea for 2-4 week rotations. They need value-added services to differentiate in a competitive charter market, and require solutions that do not disrupt standard vessel routines (compact footprint, standard vessel power connection, plug-and-play integration, and no additional time involved).
Operations and Maintenance Providers: Organisations managing turbine maintenance contracts. They need reliable damage detection data to plan repairs efficiently and meet contractual performance obligations.

All user groups share the need for reliable, rapid inspection data delivered within a 48-hour target. Hands-off autonomy and BVLOS operation, removing the need for an onboard observer, are on the commercial-phase roadmap; today the system operates with a pilot or responsible person supervising on the vessel.

Service/ system concept

The ADBISOV system consists of a drone unit installed on an SOV. When the vessel positions alongside a turbine for technician transfer, the system completes a blade inspection. Data is transferred from vessel to central teams for repair decisions to be made rapidly.

Space assets are central to the architecture. LEO satellite connectivity transfers the inspection data from the vessel to the cloud during normal operations, while GNSS with RTK corrections gives the centimetre-level positioning needed for close-range autonomous flight.

Drone control runs over a local radio link, independent of the satellite layer. This dual approach ensures both millisecond-level control responsiveness and high-volume data throughput.

The vessel equipment has a compact footprint, connects to standard vessel power, and requires no vessel modifications. Once installed, the crew initiates and monitors inspections through a web interface; the drone captures inspection imagery autonomously, with a pilot or responsible person supervising on the vessel today, and hands-off, no-touch operation is on the commercial-phase roadmap.

Space Added Value

ADBISOV relies on two space assets that are essential to its operation in offshore environments:

Satellite navigation (GNSS with RTK): The system uses GPS positioning with RTK to achieve centimetre-level positioning accuracy, enabling safe and repeatable autonomous drone flight near turbine structures. Multiple GNSS constellations are used in combination, with RTK corrections.
Satellite communications (LEO): Offshore inspections generate gigabytes of imagery per turbine. Transmitting this data to shore for AI analysis during the vessel's operational period is only feasible via LEO satellite comms, which provides significantly lower latency and higher throughput than GEO satellite alternatives.

Without satellite navigation and communications, the system would require manual piloting, data transfer by vessel to shore, or onshore connectivity, each of which would remove the cost and operational advantages the service provides.

Current Status

The project is in its early phase, with work underway across technical development, safety analysis, regulatory engagement, and market validation.

Planned demonstration activities include autonomous inspection flights at ORE Catapult's 7MW Levenmouth Demonstration Turbine in Scotland, and offshore inspections from ORE Catapult's Humber base to validate vessel motion compensation and operational performance in real conditions.

The Requirements Document was baselined at the Baseline Design Review in September 2026, with the drone platform selected and the first safety analysis complete. Integration, networking and flight testing continue towards the Critical Design Review in spring 2027.