"Aggressive Quadrotors Zip Through Narrow Windows Without Any Help" in IEEE Spectrum

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"Aggressive Quadrotors Zip Through Narrow Windows Without Any Help" in IEEE Spectrum

By Evan Ackerman 

Posted September 12, 2016

"Quadrotors are capable of doing some incredible stunts, like flying through narrow windows and thrown hoops. Usually, when we talk about quadrotors doing stuff like this, we have to point out that there are lots of very complicated and expensive sensors and computers positioned around the room doing all of the hard work, and the quadrotor itself is just following orders.

Vijay Kumar’s lab at the University of Pennsylvania is often responsible for some of the most spectacular quadrotor stunts, but their latest research is some of the most amazing yet: They’ve managed to get quadrotors flying through windows using only onboard sensing and computing, meaning that no window is safe from a quadrotor incursion. None. Anywhere. You’ve been warned.

When you watch quadrotors flying indoors, if you look closely, you’ll almost always see a motion-capture system in the background: Arrays of external cameras mounted on the walls that work together to collect very precise positional information hundreds of times every second. In this screenshot, you can see part of the camera array, with active IR emitters glowing a scary red to illuminate reflective markers mounted on the quadrotor:

With the data that a system like this provides, a computer has no problem issuing very precise commands to a quadrotor flying under remote control to get it to do just about whatever you want. The quadrotor itself is “dumb”: it has no idea where it is or what it’s doing, it’s just following orders, and is completely reliant on all of that external infrastructure to tell it what to do. This new video is different. With research by Giuseppe Loianno from Professor Kumar’s lab, along with Gary McGrath and Chris Brunner from Qualcomm, it features a (very small) quadrotor that’s smart enough to use its own sensors and onboard computation for localization, state estimation, and path planning, allowing it to perform stunts without any help..." 

Read the Full Article Here


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