DARPA Fast Lighweight Autonomy – UPenn Phase #2 Flight

DARPA Fast Lighweight Autonomy – UPenn Phase #2 Flight

“A separate team of researchers from the University of Pennsylvania reduced their air vehicle’s size and weight to be able to fly autonomously in small, cluttered indoor spaces. UPenn’s air vehicle took off outside, identified and flew through a second-story window opening with just inches of width clearance, flew down a hallway looking for open rooms to search, found a stairwell, and descended to the ground floor before exiting back outside through an open doorway.

The platform’s reduced weight and size brought new challenges, since the sensors and computers used in Phase 1 were too heavy for the smaller vehicle.

“We ended up developing a new integrated single-board computer that houses all of our sensors as well as our computational platform,” said Camillo J. Taylor, the UPenn team lead. “In Phase 2 we flew a vehicle that’s about half the size of the previous one, and we reduced the weight by more than half. We were able to use a commercially available processor that requires very little power for the entirety of our computational load.”

A key feature of the UPenn vehicle is its ability to create a detailed 3-D map of unknown indoor spaces, avoid obstacles and ability to fly down stairwells.

“That’s very important in indoor environments,” Taylor said. “Because you need to actually not just reason about a slice of the world, you need to reason about what’s above you, what’s below you. You might need to fly around a table or a chair, so we’re forced to build a complete three-dimensional representation.”

The next step, according to Taylor, is packing even more computation onto smaller platforms, potentially making a smart UAV for troops or first responders that is small enough to fit in the palm of the hand.

Algorithms developed in the FLA program have been scheduled to transition to the Army Research Laboratory for further development for potential military applications.” –

Hardware: Yash Mulgaonkar, Morgan Quigley
Software: Kartik Mohta, Shreyas S. Shivakumar, Michael Watterson, , Mikael Arguedas, Ke Sun, Sikang Liu, Bernd Pfrommer
PIs: Vijay Kumar, Camillo J. Taylor

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