AI and Robotics Give Aircraft Inspection New Wings

A joint innovation project by Sentigrate and ACRATS Europe

Aircraft are becoming increasingly lightweight and efficient thanks to the growing use of composite materials. While safety remains an absolute priority, the aviation sector faces complex challenges: how to detect damage that is difficult to see, such as hairline cracks, and how to cope with the ongoing shortage of technical personnel.

With support from CrossRoads Vlaanderen–Nederland, ACRATS Europe and Sentigrate are developing an autonomous inspection crawler that aims to make aircraft maintenance safer, faster, and more intelligent.

Composites require a new inspection approach

More than half of modern aircraft structures are made of composite materials. “Composites are strong, lightweight, and highly resistant to corrosion, but damage such as hairline cracks or delamination is often invisible to the naked eye,” explains Rick van Opdorp of ACRATS Europe.

This poses a challenge, as inspections are still largely performed manually. Such processes are labor-intensive and prone to variation. “By automating inspection processes, we not only improve efficiency, but also make the work more attractive to a new generation of maintenance professionals,” Rick adds.

An autonomous inspection crawler

ACRATS Europe develops, assembles, and supplies inspection and repair kits for composite maintenance and is internationally active as a knowledge partner and training provider in composite manufacturing, inspection, and damage repair. Sentigrate specializes in data science and artificial intelligence, with a focus on Industry 4.0, mobility, and industrial production.Within this CrossRoads project, the two partners combine their expertise to develop an autonomous inspection crawler. The robot moves independently across the aircraft fuselage and performs inspections without manual calibration or positioning. Using ultrasonic sensors—already widely proven in aviation—the crawler detects internal damage in composite materials.

“By robotizing these sensors, we replace traditional NDT (Non-Destructive Testing) inspections with a standardized, reproducible, and digital process,” Rick explains. “This increases inspection speed and reliability while reducing the risk of human error.”

Predictive maintenance through AI

All inspection data is collected centrally and processed via a scalable data pipeline. This is where Sentigrate’s AI algorithms play a key role.

“We analyze sensor signals using machine-learning techniques to identify and quantify changes in structural properties over time,” says Gert Trekels of Sentigrate. “This enables predictive maintenance, where not only existing damage is detected, but trends can also be identified that indicate future degradation or risk.”

The prototype system will be tested on both an aircraft and a helicopter—two use cases representative of civil and military aviation applications.

Impact

According to Rick, the inspection robot enhances aviation safety by enabling faster and more accurate damage detection. It also reduces the physical strain on technicians, allowing inspections to be carried out under less demanding and safer working conditions.

The project also contributes to more sustainable transport. Composite materials reduce vehicle weight and energy consumption, but broader adoption depends on reliable inspection methods. Without them, innovation can stall. This solution helps reduce uncertainty around safety and maintenance costs.

The system is being developed in a modular way, making it applicable to other sectors where composite materials play an important role, such as wind energy and maritime applications.