Ukraine launches 'Robot Army' project for combat robots within 12 months
Bottom line
Former Ukrainian Defence Minister Mykhailo Fedorov has launched the 'Robot Army' project, aiming to field combat robots for evacuation, reconnaissance, mining, and assault roles within 12 months.
Why it matters
This signals a rapid institutionalization of ground robotics in the Ukrainian military, backed by significant EU funding, which could accelerate the deployment of advanced autonomous systems on the battlefield.
Evidence — 2 independent origins
Original text (excerpt)
🇺🇦 Украина объявила о создании "армии роботов". Экс-министр обороны Михаил Федоров объявил о запуске проекта "Армии Роботов" по аналогии уже существующей "Армии дронов". "Мы запускаем «Армию роботов». В 2022 году мы запустили «Армию дронов». Сегодня на долю дронов приходится боле
Original text (excerpt)
🇺🇦 🤖 🇪🇺 Углубляется интеграция Украины с ЕС в области внедрения новых военных технологий «Украинский кластерный альянс» (объединяет более 2500 малых и средних предприятий) стал первым украинским участником «Европейской сети оборонных регионов» (включает 132 организации из 23 стра
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← Latest findings · All findings from September 2026
History · version 1 · first published · last substantive update
Cite this finding
Robot War (2026). Ukraine launches 'Robot Army' project for combat robots within 12 months. Hetzner OSINT, 27 September 2026. https://robotwar.io/osint-hetzner/2026-09-27--ukraine-launches-robot-army-project-for-combat-robots-within-12-months/
@misc{robotwar-2026-09-27--ukraine-launches-robot-army-project-for-combat-robots-within-12-months,
title = {Ukraine launches 'Robot Army' project for combat robots within 12 months},
author = {Robot War},
howpublished = {\url{https://robotwar.io/osint-hetzner/2026-09-27--ukraine-launches-robot-army-project-for-combat-robots-within-12-months/}},
year = {2026},
note = {Hetzner OSINT finding C2}
}Grades: source reliability A–F from the channel register; information credibility 1–6 from independent origins — reposts count once. The bottom line and summary are written by the model from the cited posts; grades and source roles are rule-based. Methodology 2026-10-15.v6 · Corrections · JSON · RSS · API performance