MOSCOW, September 10. /TASS/. Geoscan has unveiled an optical navigation system for drones in conditions where satellite navigation is unavailable, the company reported.
The solution was recognized as the best in the "Autonomous Navigation" category at the Dronosapiens Games engineering and technical competition organized by the Aeronext Association, it noted.
"Geoscan Group presented an optical navigation system without GNSS (Global Navigation Satellite System) for unmanned aerial vehicles (UAVs) at the Dronosapiens Games engineering and technical competition organized by the Aeronext association. The system is designed to control UAVs during aerial photography and territorial monitoring in areas without satellite navigation. Geoscan’s solution was named the best in the "Autonomous Navigation" category based on the results of three days of testing," the statement said.
The algorithm uses data from an onboard camera: the system compares the captured images with a satellite map of the area. To navigate the intended flight zone, a feature map is generated in advance. Thus, the satellite base map is automatically downloaded from available sources.
"In our projects, we encounter satellite navigation interference, radio signal jamming, and spoofing even during flights that have been approved by all relevant authorities. The need to operate under such conditions compelled us to develop an autonomous optical navigation system. We began pilot operations of our solution earlier this year. This is now one of the key technologies for the UAV industry, without which further market development is hardly possible," Geoscan CEO Alexey Yuretsky emphasized.
During the competition, the Geoscan 201 drone autonomously took off from the launch pad and successfully completed the designated route. The operator did not manually correct the flight--the drone independently determined its position and altitude. The proposed system can be used for flights covering distances of up to hundreds of kilometers. Experts are currently developing a version of the algorithm that will be able to operate at night using a thermal imaging camera.