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Video Friday: Droneapult Launch, Robot Rope Ascender, and Spock vs. Spock

These last couple weeks have been crammed full of more robots than humans like us can reasonably be expected to handle. So, you'll have to forgive us while we wade through massive amounts of incredibly extraordinarily SUPER COOL robot stuff, and you can expect several weeks worth of brand new stuff from ICRA and more. That's not happening today, though, because of course today is Video Friday!

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JPL BioSleeve Enables Precise Robot Control Through Hand and Arm Gestures

No matter how capable you make a robot, its effectiveness is limited by how well you can control it. And until we've got this whole general autonomy thing nailed down (better not hold your breath), that means a lot of teleoperation. JPL has been working on a new gesture-based human interface called BioSleeve, which uses a [insert collective noun for sensors here] of EMG sensors, IMUs, and magnetometers to decode hand and arm gestures and map them to an intuitive robot control system.

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Kuka Robot Competition Offers 20,000-Euro Award

German robotics giant Kuka announced last week a competition designed to advance mobile manipulation applications and promote the company's youBot as a platform for robotics research. The Kuka Innovation in Mobile Manipulation Award is open to researchers from around the world, who are invited to build a new and creative application in the field of mobile manipulation, with the only requisite being that a youBot be part of the system. And the prize? The winner takes all: €20,000 in cash.

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MIT Cheetah Robot Runs Fast, and Efficiently

The Cheetah robot developed at MIT's Biomimetic Robotics Lab first grabbed our attention when the project was announced back in 2009. In the years that followed few details emerged about its progress, until finally in July 2012 the lab posted videos of the robot walking on YouTube. Now, at the IEEE International Conference on Robotics and Automation (ICRA), the MIT team has shown its cheetah-inspired robot running at a respectable 22 km/h (13.7 mph). And more: the robot has an energy efficiency that rivals that of real running animals.

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Finally: Robots Learn What 'Squishy' Really Means

Humans use all sorts of bizarre, abstract terms to describe how objects feel, and it’s endlessly frustrating to robots. Or at least, we imagine it must be. Take a word like "squishy," for example: how would you explain that feeling to a robot who experiences touch through some long series of numbers? Researchers at University of Pennsylvania's Haptics Group (part of the GRASP Lab) and UC Berkeley have developed a system to teach robots how these abstract terms apply to real-world objects, to help our mechanical friends communicate with us in a more relatable way.

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Why Teaching a Robot to Fetch a Cup of Coffee Matters

In robotics, as in life, it often takes small steps to reach a big goal.

We try to post about robotics research that’s engaging and fun, and it’s easy to look at some of what we cover and wonder why it’s at all relevant. [Editor's Note: We dedicate this post to a recent commenter named David.] Being fun and being relevant are not things that are mutually exclusive, and we put a lot of energy into finding things that have a bit of both. At the 2013 IEEE International Conference on Robotics and Automation (ICRA) this week, we spotted a good example of this: a presentation by Stanford researchers about a PR2 robot autonomously fetching a cup of coffee from a coffee shop. It’s a cool video to watch, and we’ll lay out for you why getting a PR2 to do this is advancing the field of robotics as a whole.

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Shrewbot Uses Whiskers to Map Its Environment

Robots that make maps tend to be highly reliant on vision of one sort or another, whether it’s a camera image or something off the end of the visible spectrum like a laser scanner. This is understandable: humans are adapted to use vision, so we understand it pretty well, and we can get a lot of useful information out of a visual image. Animals, on the other hand, take advantage of a much broader suite of senses, specialized for their environments. If you only come out at night, or if you live in a hole, vision is perhaps not the best solution for you, and a robot modeled after a shrew can now make maps using just tactile feedback from a prodigious set of artificial whiskers.

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This Robot's Acrobatic Leaps Are the Coolest Thing You'll See Today

Animals can jump. It’s one of the things that makes them so good at getting around. To be more specific, though, animals can generally jump in addition to whatever other method of movement that they employ. We’ve seen lots of robots that can run, and lots of robots that can jump, but with a few exceptions, there hasn’t been a lot of effective crossover, because building a robot that’s physically capable of doing both in a useful manner is not an easy task.

Now University of Pennsylvania researchers, presenting today at 2013 IEEE International Conference on Robotics and Automation (ICRA), showed what happened when they taught their RHex legged robot to jump. The results are pretty darn amazing.

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Quadrotor With Tilting Propellers Can Twist in Midair

Conventional quadrotors are what’s called underactuated robots, which means that they can move in more ways than they have independent control over. For example, they can happily yaw around to any angle you want while otherwise stationary, but if you ask them to pitch or roll, they can’t do it without also changing their position: if you try to roll a quadrotor left, the whole robot is going to fly left, and if you try to fly a quadrotor left, the whole robot is going to roll left.

Having controls coupled together like this places some restrictions on what you can do with quadrotors, but a new design presented yesterday at the 2013 IEEE International Conference on Robotics and Automation (ICRA) gets around all of that with propellers that tilt.

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IEEE Spectrum’s award-winning robotics blog, featuring news, articles, and videos on robots, humanoids, drones, automation, artificial intelligence, and more.
Contact us:

Erico Guizzo
New York City
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Evan Ackerman
Washington, D.C.

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