Quadcopters Tied to a Pole Do Cooperative Acrobatics

Remarkably, tying a quadcopter to a pole with a piece of rope is actually a really good idea

2 min read
Quadcopters Tied to a Pole Do Cooperative Acrobatics

Tying a quadcopter to a pole with a piece of rope seems like it defeats the entire point of having a quadcopter in the first place, since you’re preventing it from flying anywhere except in circles around the pole, which sounds boring.

It’s not boring.

You’ll want to watch this.

These quadcopters are topping out at more than 50 kilometers per hour while flying in a circle with a radius of just 1.7 meters. The tether is exerting over 13 gs of centripetal force to keep them from flying off into oblivion. Despite the speed, there seems to be no problem getting four quadcopters to do a bunch of coordinated acrobatics, which is fun (if a bit dizzying) to watch. I had to keep reminding myself that the vid wasn’t sped up.

The reason to do this kind of thing from a research perspective is that it’s the only way (that I can think of) to fly a quadcopter really really fast, or to subject it to a bunch of gravities, in a confined, controlled space. At ETH Zurich, the ability to do this is helping them get familiar with how quadcopters handle at very high speeds, how big of an issue drag is, the efficiency of different propeller designs, and stuff like that. Also, it gives them a chance to practice controlled maneuvering at high speed, including the emergency braking that’s featured in the vid. 

All of this is taking place in ETH Zurich’s Flying Machine Arena, and the quadcopters are being very carefully tracked with what is almost certainly a very expensive motion capture system. However, the researchers (led by Maximilian Schulz and Prof. Raffaello D’Andrea) comment that it’s possible to remove the pole completely and let quadcopters attached to each other with strings balance themselves while flying around a single point at high speeds, and that “this could be then used in performance settings, possibly enhanced by light and sound effects.” We’d pay good money for that.

“High-speed, Steady Flight with a Quadrocopter in a Confined Environment Using a Tether” by Maximilian Schulz, Federico Augugliaro, Robin Ritz, and Raffaello D’Andrea, has been submitted to IROS 2015.

[ ETH Zurich ]

Thanks Markus!

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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

11 min read
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
LightGreen

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

"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.

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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