Scientists at the University of Southampton test a drone with its own nervous system

Experts at the University of Southampton have developed a drone with a nervous system . This drone is equipped with a fibre optic system that acts as a “nervous system”, allowing it to operate more autonomously and for longer periods of time. This technology, which simulates human nerves, is based on optical fibres that send information about the status of the drone in real time, thus reducing the need for frequent stops for manual inspection.

How does the drone with nervous system work?

The system was created by Dr Chris Holmes and Dr Martynas Beresna, researchers at Southampton’s Optoelectronics Research Centre. The technology relies on a process called optical speckle, which projects images that detect stresses and potential faults. These signals can then be interpreted by artificial intelligence algorithms, alerting the ground team to the status of the drone without interrupting its flight.

It’s as if the drone has its own nervous system, using light instead of electricity, which avoids radio interference.

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Dr. Holmes explained.

Testing the drone with a nervous system. Source: University of Southampton

A monitoring system for an expanding industry

The drone sector promises to contribute up to £45 billion to the global economy by 2030, with a considerable impact on logistics and transport. This new system seeks to take advantage of that growth, offering diagnostic technology that can be applied to commercial drones, optimising their flight time and safety . Toby King-Cline, an aerospace engineer, led the team of students who tested the system on a drone designed to carry emergency equipment.

The technology could transform the way we operate drones across multiple industries.

Toby added.

The research team hopes to bring this system to market by 2025, with the support of the university’s Future Worlds acceleration programme. The scientists believe their innovation will enable drones of the future to be safer, more cost-effective and more reliable, highlighting their potential for large-scale commercial applications.

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Source and photo: University of Southampton