Fast Lightweight Autonomy (FLA) program

[Airicist]

darpa.mil/program/fast-lightweight-autonomy (https://www.darpa.mil/program/fast-lightweight-autonomy)

GRASP Laboratory (https://pr.ai/showthread.php?1008)

[Airicist]

https://youtu.be/H6H2SOiJPVE

Fast, Light and Autonomous Quadrotors

Uploaded on Nov 2, 2015


The University of Pennsylvania’s GRASP Laboratory has received a three-year, $5.5 million grant from DARPA, the Defense Advanced Research Project Agency, to create new flying robots that are able to quickly and autonomously navigate unknown environments. These abilities would be invaluable in disaster situations where conditions are too dangerous for humans to inspect damage or search for trapped or injured people.

[Airicist]

Article "Penn’s GRASP Lab Receives $5.5 Million for ‘Fast, Light and Autonomous’ Flying Robots (https://penntoday.upenn.edu/news/penn-s-grasp-lab-receives-55-million-fast-light-and-autonomous-flying-robots)"

by Evan Lerner
November 3, 2015

[Airicist]

https://youtu.be/LaXc-jmN89U

Fully Loaded Quadcopter Achieves 20 m/s Flight

Published on Feb 12, 2016


DARPA's Fast Lightweight Autonomy (FLA) program recently demonstrated that a commercial quadcopter platform could achieve 20-meters-per-second flight while carrying a full load of sensors and cameras. The FLA program aims to develop and test algorithms that could reduce the amount of processing power, communications, and human intervention needed for unmanned aerial vehicles (UAVs) to accomplish low-level tasks, such as navigation around obstacles in a cluttered environment. If successful, FLA would reduce operator workload and stress and allow humans to focus on higher-level supervision of multiple formations of manned and unmanned platforms as part of a single system. Through this exploration, the program aims to develop and demonstrate the capability for small (i.e., able to fit through windows) autonomous unmanned aerial vehicles to fly at speeds up to 20 m/s with no communication to the operator and without GPS.

[Airicist]

https://youtu.be/g1HqhCiNdQU

Smart Quadcopters find their way without human help or GPS

Published on Jun 28, 2017


Phase 1 of DARPA’s Fast Lightweight Autonomy (FLA) program concluded recently following a series of obstacle-course flight tests in central Florida. Over four days, three teams of DARPA-supported researchers huddled under shade tents in the sweltering Florida sun, fine-tuning their sensor-laden quadcopter unmanned aerial vehicles (UAVs) during the intervals between increasingly difficult runs. DARPA’s FLA program is advancing technology to enable small unmanned quadcopters to fly autonomously through cluttered buildings and obstacle-strewn environments at fast speeds (up to 20 meters per second, or 45 mph) using onboard cameras and sensors as “eyes” and smart algorithms to self-navigate.

"Smart Quadcopters Find their Way without Human Help or GPS (https://www.darpa.mil/news-events/2017-06-28)"
Milestone series of tests have quadcopters slaloming through woodlands, swerving around obstacles in a hangar, and reporting back to their starting point all by themselves

June 28, 2017

[Airicist]

https://youtu.be/_UFabSMuz6w

DARPA's Fast Lightweight Autonomy (FLA) technology explained

Published on Jun 28, 2017


DARPA FLA researchers discuss their unique approaches to achieving autonomous flight without GPS or remote control (RC) communication links.

[Airicist]

https://youtu.be/nVbZjbm4i84

DARPA Fast Lighweight Autonomy - UPenn Phase #2 Flight

Published on Apr 12, 2019


"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."

"Faster, Lighter, Smarter: DARPA Gives Small Autonomous Systems a Tech Boost (https://www.darpa.mil/news-events/2018-07-18)"
Researchers demo latest quadcopter software to navigate simulated urban environments, performing real-world tasks without human assistance

July 18, 2018