A precision-landing system that uses AI to detect a helipad "H" marking and lands the drone exactly on its centre — continuously re-centring during descent so wind/drift cannot throw it off. My first serious international freelance job.
Tech stack
A precision-landing system I delivered in ~2-3 days for an international client via Upwork/Fiverr — my first serious paid international freelance job. A downward-facing camera on the drone detects the helipad "H" marking in real time, and the system brings the drone to the exact centre of that marking before touching down.
It had to land on the exact centre of a helipad whose position is not known in advance (variable), despite wind and drift. Landing on a fixed GPS point isn't enough — the target can shift at the moment of touchdown.
I detect the "H" with a custom single-class YOLOv3-tiny model (on OpenCV's DNN module). It picks the largest box (nearest pad), finds its centre and computes the offset from the camera centre. A control loop with a dead-zone threshold issues short body-frame (NED) velocity commands (DroneKit + MAVLink) to close the offset. Once centred enough, it switches to ArduPilot LAND mode; it keeps tracking the "H" throughout the descent, makes corrective manoeuvres if it drifts, and disarms the motors on ground contact.
I delivered an end-to-end system running in Gazebo + ArduPilot SITL that performs the whole takeoff–search–centre–autonomous-landing loop (demo video on the cover). Since the architecture is DroneKit/MAVLink, it ports to a real ArduCopter vehicle.
I can deliver, fast, a vision-based system that detects the target and lands dead-centre despite wind.
Tell the assistant what you need — we will talk through whether I can build something like this, the approach and the free first step right away, and it books a time that suits you.
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