Automation
5 posts in this category.
Computer vision in drones: object detection, tracking, and recognition explained
Computer vision is the perception engine inside every modern autonomous drone. From YOLO object detection to ByteTrack tracking and EO/IR target recognition on a Jetson Orin payload. The Indian computer-vision-in-drones stack has shifted from imported subsystems to indigenous detection-and-recognition payloads.
Read article →Manned-unmanned teaming: doctrine and Indian programmes
Manned-unmanned teaming is the doctrine where a piloted aircraft commands a formation of unmanned platforms that scout, jam, decoy, relay sensor feeds, or strike. India is now building four loyal-wingman tracks across the Indian Air Force, Indian Army, and Indian Navy under a single tri-service MUM-T framework.
Read article →Drone swarms and how swarm intelligence actually works in modern warfare
Drone swarms turned single-platform unmanned warfare into collective decision-making at machine speed. This piece walks the swarm intelligence stack, the algorithms behind it, the architecture classes, and the indigenous Indian programmes heading into the sovereign swarm RFP.
Read article →AI in drones: how artificial intelligence makes UAVs autonomous
AI in drones has shifted unmanned aerial vehicles from remotely piloted machines to autonomous platforms that perceive, decide, and act with limited human input. This is the analytical reference on the autonomy stack, the Indian programme map, and the doctrine shift now driving India's drone-centric force structure.
Read article →AI and autonomous drones: how unmanned systems think and act
Autonomous drones now anchor military modernisation, BVLOS inspection, and contested-environment operations across India. This explainer walks the full autonomy stack end to end: how unmanned systems perceive, decide, act, coordinate as swarms, and navigate when GPS fails. It closes on where India's indigenous edge-autonomy programmes stand today.
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