Pilot & Liferay
Pilot
Have you ever looked at the old maritime navigation charts and wondered how they could be turned into a modern flight‑planning tool?
Liferay
I’ve taken a chart, parsed every latitude‑longitude pair into a node list, then treated the old routes as weighted edges. Running Dijkstra or A* on that graph gives you a shortest‑flight path that still respects the classic navigation constraints. Then overlay the result on a modern map tile layer so you get a flight‑planning UI that looks contemporary but is built on the same data the mariners used.
Pilot
That’s a neat way to bridge old and new. It’s like giving the sea‑carriers a jet‑pack – you keep the tried‑and‑true waypoints, but the route gets a modern lift. If you add a bit of wind or turbulence data on top, you’ll get an even more realistic flight plan. Nice work!
Liferay
Sure, just overlay a vector field of wind on the edge weights. It’ll make the route more realistic but also introduce discontinuities if you don’t interpolate the wind data smoothly.
Pilot
Smooth wind data is key – think of it like a well‑tuned engine. If you keep the field continuous and maybe use a simple bilinear interpolation between grid points, you avoid those nasty jumps. That way the pilot can trust the path and the aircraft can glide through the sky without any unexpected bumps.
Liferay
Bilinear interpolation is fine, but the grid resolution is the real limiter. If your grid cells are larger than the aircraft’s step size, you’ll still get small jumps. Aim for a 5‑10 km grid and apply a simple moving‑average filter afterward to kill the remaining high‑frequency noise. That gives the pilot a truly smooth path without those “unexpected bumps.”