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This Crazy Technology Brings 'Dr. Octopus' to Real Life (Sort Of)

These robotic, claw-tipped arms were actually designed for a reason that might surprise you.
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Here's another for the "we're living in the future, and it is a creepy, creepy place" files: German engineers have developed a bionic tentacle which can learn and remember actions and situations.

Remind you of a certain crazy foe of Spiderman named Dr. Octopus? Yeah, we were thinking the same thing.

While this may raise the heart rates for some comic book fans, this robotic appendage was actually designed to help with much more mundane tasks like picking fruit or replacing light bulbs -- tasks which, until now, were typically done by humans because they involve incredibly complex, minute actions and adjustments to be done properly. After all, an apple is never in exactly the same place from tree to tree, and you can't use brute force to grab a piece of fruit without damaging it.

German engineering firm Festo designed the appendages, which are meant to bring the dexterity of an elephant's trunk to industrial robots. Each trunk is formed of 3-D printed segments controlled by an array of pneumatic artificial muscles. The fascinating part, though, is that these robots aren't delivered with complex, precision control software. Instead, they actually learn what they are supposed to do through trial and error.

It's a process called " goal babbling," and it's thought to be similar to the way a baby learns how to grab objects by continually reaching, failing, and making minute adjustments until they get it right. It's a process of trial and error that lets them figure out which muscles to move in which ways to achieve their goal. Essentially, the scientists have figured out a way to give a robot the same sort of muscle memory humans (and other creatures) have.

Here's a video, via New Scientist, that shows the appendages in action:

One of the reasons that ability to learn is so important is because it eliminates the need for highly-trained experts in robotics and programming to teach the robot how to do its job. Instead, the devices can be used with minimal programming, making them much more widely-useful in the real world. 

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