Inside Google's Secret Drone-Delivery Program

The tail-sitter configuration, in which the whole craft rotates from a vertical to a horizontal position, has also been a source of fascination through aeronautical history. The Nazis, for example, were considering such a craft. And there was an American defense program that resulted in the creation of two prototype aircraft by Lockheed and Convair. The photographs of these huge planes sitting vertically on runways—shiny and steel, unmistakably mid-century—feel retrofuturistic. None of the research efforts caught on, though, with a major problem being that there wasn’t a good way for the pilot to deal with the change in orientation.

The Lockheed XFV-1 tail sitter (US Navy).

Obviously, that’s not a problem with a drone, though. The “pilot” is housed in a desktop-class computer that sits towards the tail of the plane. The power system, batteries, cabling, and a big capacitor, sit just above it. That’s hooked to the motors, which also send back motor performance data to the flight computer. Sensor data also comes in from the inertial measurement unit (IMU) mounted to the left of the computer. The IMU uses accelerometers and gyroscopes to determine the X-Y-Z positioning of the craft, an essential part of flying. In the nose, we find the GPS unit, and in the tail, there’s a camera pointed down. There’s no on-board laser rangefinding system in the current incarnation, but there are two communications radios, one high-bandwidth for sending telemetry data, and one low-bandwidth for longer range communications.

Google has not settled on this design for all its future program development, but it has formed the platform for much of their testing. While the hardware is a significant part of the problem, they seem largely agnostic about which flying machine might ultimately serve their needs best. The real challenges, Teller and Roy insist, come in the design of the rest of the system like, for example, the delivery mechanism.

Imagine all the possible ways one might get something from high in the air down to the ground. How about a tiny parachute à la The Hunger Games? Roy’s team tried it. There was too much wind interference and they struggled with accuracy. How about literally firing them down, a ballistic approach? “We contemplated this,” Roy said. “And then Sergey walked out from under a balcony and we almost hit him in a drop test.” After that, they moved on.

Another obvious idea is to simply land the craft, drop the package, and then take off again. To test the premise, they brought in some of Google’s user experience researchers who queried people about how they might react to such a delivery.

What they found was that individuals could not be stopped from trying to reach for their packages, even if they were told that the rotors on the vehicle were dangerous, which they are.

Finally, they settled on an idea that Roy had initially resisted: winching down a line with the package on it and then winding it back up into the craft.

Mechanical engineer Joanna Cohen, trained at Cal Tech and MIT, designed the contraption. It consists of a few key parts. The first is the winch itself, which spools out the hi-grade fishing line. The second is the “egg,” the little gadget that goes down with the package, detects that it has reached the ground, releases the delivery, and signals that it should be cranked back up to the hovering UAV. If something goes wrong, there is an emergency release mechanism at the top of the line—“basically a razor blade,” Cohen told me—that allows the UAV to cut and fly.

When a package comes hurtling down, it moves at about 10 meters per second (about 22 miles per hour). When it gets close to the ground, the winch slows the fall to 2 meters per second for a relatively soft landing.

In the abstract, or under ideal conditions, this seems simple enough. But the project’s hardware lead James Burgess said that out in the world, it’s not so easy to make the deliveries work.

“If you can imagine a user case where we’re going to someone’s house, and the egg hits something—maybe it hit the power lines, maybe it hit the trees, maybe it hit the roof, maybe it hit the railing on the porch before it got to the porch. There are a lot of unknowns and environmental challenges,” Burgess said.

“So the egg is smart enough to know that it hit something, but the vehicle also knows how high it is and the winch also knows how much line it is letting out. The egg says, ‘I hit something,’ and the vehicle says, ‘But wait, you’re not far enough down yet, so keep going because probably you bounced off something and don’t arm yourself for [package] release.’ So, all of our sensors and components work together in this network to make good decisions.”

Or, for now, some kind of decision. When I asked how they planned to deal with power lines, which seem especially challenging to sense and avoid, the whole team demurred. “Remember: early days,” Roy intoned. “We’re not even close to that.”

* * *

Like all autonomous robots, delivery drones have three fundamental tasks. They have to understand their position in the physical world. They have to reason where they should go next. And they have to actually execute the control maneuvers to get there.

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