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No GPS Required: Drones Can Now Identify Objects From a Kilometer Away

Drone identifies objects without GPS
Без необхідності GPS: Дрони здатні виявляти об'єкти з відстані до одного кілометра. Photo: НВ — Техно

RangeMark visual recognition system passes field tests

According to НВ — Техно: On August 7 at 9:01 AM, Sodyo announced that its RangeMark visual identification system had completed successful trials. The technology lets a drone spot markers while traveling at speeds of up to 20 meters per second, with reliable detection out to 500 meters. RangeMark also works at a maximum distance of one kilometer for passive visual markers, relying solely on an ordinary camera. No GPS, radio-frequency links, cellular networks, or other external connectivity are involved.

Test outcomes and next steps

In the trials, drones detected a one-meter marker from as far as 500 meters away, while 50-centimeter markers remained visible at a distance of 250 meters. A single camera frame can cover an area of roughly 20 hectares. Since operators can place battery-free printed markers on an object or in a designated zone, the system is especially practical for hover, transit, and search operations.

Sodyo intends to license RangeMark to drone makers, autonomous navigation platform developers, camera suppliers, and systems integrators. The technology will make its public debut at Commercial UAV Expo Americas 2026, scheduled for September 1–3 at Caesars Forum in Las Vegas.

"Knowledge is what is needed," said Alon Raz, emphasizing the importance of new technologies for unmanned aerial vehicles.

Visual identification systems like RangeMark are increasingly important for improving drone performance across applications from surveillance to rescue missions. Because it can recognize markers without GPS or other external signals, this kind of system may prove essential in environments with limited connectivity or navigation infrastructure. With GPS jamming and outages a growing concern, visual alternatives like RangeMark are becoming more relevant.

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