Wind turbine rotor blades are getting larger, more complex and more demanding to inspect. Many defects develop deep inside the composite structure and remain invisible for a long time when using conventional inspection methods. Once damage reaches the surface, repairs are often significantly more expensive and time-consuming.
This is where the InInspekt research project comes in. The consortium brings together the Federal Institute for Materials Research and Testing (BAM), the University of Würzburg, EduArt Robotics and the AI specialist LATODA. The goal is to modernise internal rotor blade inspection with a mobile robotic system that can detect relevant anomalies earlier and document them more precisely.
EduArt Robotics is contributing the mobile robot platform and project coordination. The system is being designed for operation inside hard-to-access blade interiors, where manual inspection is difficult, slow and physically demanding. According to the project partners, the robotic approach is intended to reduce inspection effort while improving consistency and data quality over long operating periods.
The technical concept combines several sensing modalities. A LiDAR-based system supports navigation and geometric localisation inside the blade. In addition, the inspection unit uses measurement cameras, a colour camera and thermography to capture both visible and subsurface defects. The University of Würzburg is developing key parts of the sensing and measurement setup, including a movable unit for precise alignment of the mounted sensor package.
The generated data is then processed using AI-supported image analysis. The aim is not only to detect anomalies, but also to classify them, assign them spatially and prepare them for long-term condition assessment. This creates a foundation for more informed maintenance decisions and can help extend the service life of wind turbine blades.
InInspekt started on 1 December 2025 and is scheduled to run for two years. The project is funded by the German Federal Ministry for Research, Technology and Space (BMFTR) within the programme Digital Green Tech – Environmental Technology meets Robotics. The topic will also be presented by BAM at Hannover Messe from 20 to 24 April 2026.
For EduArt Robotics, the project is a strong example of how mobile robotics, robust sensor integration and practical AI can support critical inspection tasks in the energy sector. Or, to put it less formally: sometimes the smartest place for a robot is inside a wind turbine blade.