It’s amazing to me that many of the proposals I’m hearing for drone ATC are based on the current human pilot and human air traffic controller-based system. You know, the system that can only handle very limited air traffic, and breaks down every time there are budget problems.
There is no reason to adopt this system for drones. We now have a chance to invent a decentralized, automatic, and scalable system for drone ATC. If drones are produced in the vast fleets I imagine they will be, then this will become the de facto ATC system and the old control tower system will just be background noise.
I have not designed a complete drone ATC system. However, here are a few attributes I think it should have:
– Distributed and Local. There’s no reason a slow flying drone should worry about traffic hundreds of miles away. The air traffic the drone monitors should be self-limited in range depending on the drone’s characteristics. The ATC system need not be centralized: local drones can figure out how to share airspace themselves.
– Cooperative. The drone behavior model should be: I’ll head directly to my destination but will make small adjustments to avoid hazards and collisions.
– Anonymous. Much bandwidth in the current ATC system is dedicated to identifying aircraft, their class, their size, their cargo, and so forth. The purpose of this is to aid a human in a centralized ATC system to prioritize and manage air traffic. With swarms of drones flying, none of them cares about the others’ name or ICAO registry number. All they should care about is how to get to their destination safely by sharing airspace, without centralized controller assistance.
– Negotiated. Much like a communications bus protocol, drones could negotiate for the use of the limited resource (airspace). A drone can reserve a slot in space and time (their trajectory) and make small concessions to allow other drones to pass. Drones that are unable to maneuver quickly could “insist” on the trajectory they need to use.
I isolated and slowed down the few flyby frames from the Hawaiian hawk (‘io) swooping by our quadcopter.
Here’s a link to the short slow-mo segment.
A Hawaiian ‘io hawk decided to check out the quadcopter drone today as it was flying around, testing out some automated takeoff and landing.
The ‘io first circled the rising drone a couple times and then came in close enough for the cheap camera on the drone to capture a closeup image. I then turned the drone’s camera to face the gulch trees as the ‘io landed in them.
It was a short, exciting encounter — I wasn’t sure what to expect from the ‘io. Would the hawk attack the drone or just inspect it? In the end the ‘io landed in the trees and preened, apparently satisfied that the drone was harmless.
Automated flight using 12 circular waypoints in a rough circle. Also experimented with altitude and yaw adjustments along the way (these were preprogrammed into the waypoints). You’ll notice that the drone pauses at some waypoints and not others– I wanted to look at some views I hadn’t been able to see before because the camera is fixed the the front of the drone.
I’ve been experimenting with Ardupilot’s automated quadcopter flight modes and the andropilot app for android devices. Today I flew a simple loop over our pasture with a few waypoints.
Here’s a video of automated flight over Papaikou Orchardand the flight path traced out in Google Maps.
You can see the main town of Papaikou (about 9 miles north of Hilo, on the Big Island of Hawaii), and when the quad returns for a landing you can see giant Mauna Kea in the distance.