VertiKUL UAV Explores Practicalities of Delivery Drones

Autonomous landings, cargo management, and range: this drone is trying to do it all

2 min read
VertiKUL UAV Explores Practicalities of Delivery Drones
Autonomous landings, cargo management, and range: this drone is trying to do it all.
Photo: KU Leuven

We’ve been skeptical about delivery drones ever since Amazon made it sound like delivery drones were 1.) easy and 2.) right around the corner. Realistically, there’s a huge amount of stuff that has to happen before delivery drones can work in practice; a lot ofit isregulatory, but there are technical problems to be solved as well. Researchers at KU Leuven, in Belgium, have been working on some of these, including landing pads, cargo compartments, and range extension.

Take-offs and landings are probably going to be the trickiest part of this whole delivery drone business, and a landing pad is likely a necessity. These pads have optical patterns on them to enable precision visual landings, and arrays of LEDs light them up at night. Once the UAV gets close enough (GPS close), it can home in on the pad and make a touchdown.

Since the landing pads are, if everything goes well, the only points at which the UAV will interact with the ground, they need to provide all of the ground support that’s necessary for the vehicle to operate autonomously. I like the fact that the loading mechanism (and the UAV itself) completely protects the payload from inclement weather, although the roboticists who are developing this system (a group of graduate students at KU Leuven) are still working on getting it all to work well in wind.

The UAV itself can transition between vertical and horizontal flight, which addresses one of the big problems with rotorcraft: terrible terrible range. It’s great that quadcopters and other drones powered by rotors can do all that fancy hovering and stuff, but there’s a reason why we all get crammed into airplanes to fly anywhere: passive wings that generate lift without having to rapidly spin in circles are much more efficient.

We don’t have data from KU Leuven on how much more efficient the robot is, but we do know that it currently has a 30 kilometer range, and that it’s scary fast: “We did not yet lower the pitch up to an optimal angle of attack (about 7 degrees) because then it flies too fast out of view.” Awesome. When it’s vertical, though, those wings are probably a big part of the reason why the researchers are finding it difficult to control the robot when it’s windy. It’s a compromise, certainly, but a necessary one, since more range means fewer base stations and cheaper overall system.

The missing piece here is either a charging infrastructure or a way to swap batteries, but we’re confident that by the time these guys get their Ph.Ds, they’ll have that convincingly solved.

[ KU Leuven ]

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How the U.S. Army Is Turning Robots Into Team Players

Engineers battle the limits of deep learning for battlefield bots

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Robot with threads near a fallen branch

RoMan, the Army Research Laboratory's robotic manipulator, considers the best way to grasp and move a tree branch at the Adelphi Laboratory Center, in Maryland.

Evan Ackerman

“I should probably not be standing this close," I think to myself, as the robot slowly approaches a large tree branch on the floor in front of me. It's not the size of the branch that makes me nervous—it's that the robot is operating autonomously, and that while I know what it's supposed to do, I'm not entirely sure what it will do. If everything works the way the roboticists at the U.S. Army Research Laboratory (ARL) in Adelphi, Md., expect, the robot will identify the branch, grasp it, and drag it out of the way. These folks know what they're doing, but I've spent enough time around robots that I take a small step backwards anyway.

This article is part of our special report on AI, “The Great AI Reckoning.”

The robot, named RoMan, for Robotic Manipulator, is about the size of a large lawn mower, with a tracked base that helps it handle most kinds of terrain. At the front, it has a squat torso equipped with cameras and depth sensors, as well as a pair of arms that were harvested from a prototype disaster-response robot originally developed at NASA's Jet Propulsion Laboratory for a DARPA robotics competition. RoMan's job today is roadway clearing, a multistep task that ARL wants the robot to complete as autonomously as possible. Instead of instructing the robot to grasp specific objects in specific ways and move them to specific places, the operators tell RoMan to "go clear a path." It's then up to the robot to make all the decisions necessary to achieve that objective.

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