Russian AI Lets Farm Machinery Ditch GPS

When satellites go dark, the combine harvester switches to cameras and neural networks

In Russia’s agricultural tech sector, GPS isn’t the only way forward anymore. Engineers are now testing an AI-driven autonomous navigation system that uses machine vision to guide combine harvesters — even when satellite signals drop.

The system relies on a suite of cameras mounted on the vehicle and real-time video analysis. If GPS fails, the onboard neural network takes over, using the video feed to keep the machine aligned with its route, row by row — no human required.

This cutting-edge “parallel driving” technology is currently being field-tested on rapeseed and wheat farms, with researchers from the Kuban State Agrarian University closely monitoring results. The AI continuously maps out the harvester’s trajectory and makes split-second corrections, ensuring precise movement and maximum yield efficiency — even in signal dead zones.

“We plan to adapt the system for tractors and test it during spring soil preparation,” university officials said.

According to recent data, over 90% of Russian farmers experience GPS disruptions. This homegrown, machine vision–based platform could become the answer — offering a new level of independence from satellite infrastructure in one of the world's most tech-hungry industries.