FlipBot Is Why Your Car Needs a Tail
Image: Amir Patel

Cars are almost, but not quite, entirely incapable of acrobatics. We need to solve this. I'm not sure why we need to solve this, but we do, and the good news is roboticists are on it.

Following up on some work from last year on putting actuated tails on ground vehicles (inspired by other tailed robots like UC Berkeley's Tailbot), researchers from the University of Cape Town, in South Africa, have put a tail on a small RC car and gotten it to do a barrel roll.*

Inspired by the acrobatics of the lizard, we present a novel robot platform capable of performing a barrel roll from a ramp. The system is modeled using Euler-Lagrange mechanics, followed by controller design and numerical simulation. A robotic platform is then designed to perform the experiments. Finally, we show that purely by the use of the actuated tail, the robot can rapidly perform a 360 degree roll rotation in under a second.

I know, you're thinking, "Oh, what, a barrel roll? No big deal. I could totally do that. James Bond has done it, so how hard could it be?"

For the Bond movie, a stuntman supposedly performed the trick in the first (and only take) while eight cameras captured the scene from different angles and a team of divers and ambulances waited nearby in case something went wrong.

As far as we know, nobody has tried to do this in a movie ever since. Even Top Gear couldn't pull it off properly:

So, let's get on this: Top Gear, MythBusters, somebody: for the love of all that is incredibly awesome, put an actuated tail on a car and see what you can do with it.

"FlipBot: A Lizard Inspired Stunt Robot," by Callen Fisher and Amir Patel from the University of Cape Town, South Africa, will be presented next week at the 19th World Congress of the International Federation of Automatic Control.

* If you haven't yet Googled this phrase, you should try it.

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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
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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