The Ministry of Electronics and Information Technology (MeitY) with Drone
Federation of India, has introduced NIDAR 2.0 (2026-27) under the SwaYaan initiative to
build indigenous drones and flight controllers powered by India’s homegrown VEGA
processor. This innovation reduces reliance on foreign chips, strengthen the
domestic drone and electronics manufacturing ecosystem. This initiative aims to
accelerate the development of next-generation unmanned aerial system (UAS) by
encouraging startups, researchers, and industry to build drones using domestically
manufactured electronic components.
NIDAR 2.0 stands for National Innovation Challenge for Drone Application and
Research that aligns with government’s vision of Atmanirbhar Bharat, the India
Semiconductor Mission (ISM), and the Designed Linked Incentive (DLI) Scheme. The
goal of this hackathon is to provide a valuable opportunity for students and working
professionals to build flight controller and autopilot hardware powered by India’s
indigenous VEGA microchip.
According to MeitY release, NIDAR 2.0 offers a prize pool of more than 65 lakh that
not only promote innovation but also supports startups, nurtures young talents, and
accelerate the development of domestic drones and semiconductor technologies
through incubation, technical mentorship, and industry collaboration.
Launching the challenge, MeitY Secretary S Krishnan said, “NIDAR 2.0 takes our
students from just flying drones to building the drone’s brain. When the drone’s
brain runs on India’s own VEGA processor, we are not just training engineers. We are
laying the foundation of a self-reliant drone industry.”
The primary focus of this hackathon is to build autonomous swarm drones capable of
locating survivors and delivering medical supplies in disaster-hit areas without an
external communication network, and developing GPS-denied drones for indoor
industrial inspection. By collaborating as a coordinated fleet, swarm drones can
rapidly survey large areas, identify victims using onboard sensors and AI-based image
processing, and optimizing search-and-rescue operations without relying on constant
human intervention.
