UAVOS, supported by the company’s Engineering Service, has successfully tested its autopilot system using computer vision.
For the testing, the UAVOS avionics system was integrated into the company’s cutting-edge unmanned helicopter. The autopilot system leveraged advanced computer vision and AI to navigate the unmanned aerial vehicle (UAV) in GNSS-denied environments with precision and reliability.
The onboard computer vision-based alternative navigation module with deep learning algorithms provided the UAVOS avionics system with the geospatial coordinates.
Computer vision enabled accurate, resilient navigation during both day and night, offering safe take-off and landing independent of the UAV. This method for acquiring and processing enabled the drone to ‘see’ and interpret its environment, allowing it to navigate autonomously without needing GNSS.
The use of computer vision in drone navigation systems is an advanced approach that aims to set up new standards for autonomous drone navigation and safety.
Aliaksei Stratsilatau, CEO of UAVOS, commented,“Our engineering support of this project will help our clients to leap forward in drone technology. By enabling truly autonomous flight in complex environments, we are empowering businesses and organizations to leverage drones in new ways. This technology is not just about improving efficiency; it’s about fundamentally changing how we approach tasks that were once too dangerous or difficult for humans to undertake.”
