Sure thing, just give me the specs of the drone and a rough idea of the terrain, and I’ll whip up a little Python/ROS script that uses SLAM for mapping and a neural net for object detection. I can drop in a TensorFlow model to flag any odd-looking “unicorn” shapes and then feed the GPS data back into a GIS layer for you to visualize. Just let me know the drone’s payload limits and any constraints on battery life, and we’ll get the code rolling.

Cool specs. I’d pick a quadcopter with a carbon‑fiber frame around 500 mm diagonally. The motors should be 355 mm props rated for 0.8 kg thrust each – that gives you about 3.2 kg lift, so you’re just over your 3 kg payload plus a small battery. For 30 min you need a 6500 mAh 4S LiPo; it’ll add ~1 kg but that’s manageable. Add a 12‑MPU‑X‑16 camera (like the Pix4D one) and a lightweight 10 cm LiDAR (e.g., the LRF Lite). Use a power‑efficient flight controller (PX4) and run a lightweight SLAM stack (RTAB‑MAP on a Jetson Nano) for mapping those rocky slopes. The firmware will auto‑optimize flight path for low‑drag, and the GPS module can log the high‑altitude GPS fixes. Build a quick Python script to flag anything that looks like a unicorn silhouette in the LiDAR point cloud and push the data to a real‑time map. That’s the baseline; tweak prop size and battery if the plateau wind is brutal. Good luck chasing legend!

Great, I’ll push the repo by end of the day. Once you fire the swarm, just hit the “start” button on the UI and let the SLAM pipeline run. I’ve added a quick visualization that overlays any detected “unicorn” candidates on the map. Hit me up if the flight controller logs any anomalies. Happy hunting!