Militarnyi has reported that the ZIR System company has developed an artificial intelligence-powered system that enables drones to automatically identify and target objectives. Currently, developers are focused on improving the system’s accuracy, after which they plan to codify it for procurement by Ukraine’s Defense Ministry.
In recent months, Russia has intensified its drone attacks on Ukraine, utilizing various types of drones, including Iranian-made Shaheds, to strike critical infrastructure and urban areas. Conversely, Ukraine has also ramped up its drone capabilities, launching long-range strikes deep into Russian territory. Notable attacks have targeted military facilities and logistics hubs, demonstrating Ukraine’s growing proficiency in drone technology.
Unlike traditional computer vision systems in kamikaze drones, the ZIR system not only guides the drone to determined targets but can independently identify enemy assets.
The AI technology for drones was trained using a specially created database and can currently recognize seven types of targets: infantry, cars, minivans, trucks, air defense systems, artillery, armored vehicles, and tanks.
According to the company, the system can even detect equipment hidden in forested areas. It can be installed on any FPV kamikaze drone, regardless of its type—whether it is a multicopter, wing, or plane. It comes equipped with its own camera and connects to the flight controller and standard VTX module. A drone is operated by a standard remote control.
The system’s target recognition range varies from 150 to 800 meters, depending on the target type, while the automatic targeting range reaches up to 1,000 meters.
Additionally, it can detect and track multiple targets simultaneously, allowing the operator to select which one to engage. The AI also helps a drone target moving objects at speeds of up to 60 kilometers per hour.
The manufacturer is also developing a system for interceptor drones. Although the software is already ready, a final product is still being developed.
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