DARPA Developing Algorithms for Fast, Lightweight & Autonomous UAVs

Posted by Betsy Lillian on February 16, 2016 No Comments

The Defense Advanced Research Projects Agency (DARPA), an agency of the U.S. Department of Defense, has kicked off its fast lightweight autonomy (FLA) program, which 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, says DARPA, FLA would reduce operator workload and stress, as well as allow humans to focus on higher-level supervision of multiple formations of manned and unmanned platforms as part of a single system.

According to DARPA, FLA technologies could be especially useful to address a pressing surveillance shortfall: Military teams patrolling dangerous overseas urban environments and rescue teams responding to disasters can currently use remotely piloted UAVs to provide a bird’s-eye view of a situation; however, to know what’s going on inside an unstable building or a threatening indoor space, the teams often must put themselves in danger through physical entry.

The FLA program develops algorithms aimed at enabling small UAVs to quickly navigate a labyrinth of rooms, stairways and corridors or other obstacle-filled environments without a remote pilot. The program seeks to develop and demonstrate autonomous UAVs small enough to fit through an open window and able to fly at speeds up to 20 m/s (45 mph) while avoiding objects within complex indoor spaces – independent of communication with outside operators or sensors and without reliance on GPS.

DARPA researchers recently completed flights with a quadcopter that three research teams are using for the program. The test data validated that the platform – which uses a DJI Flamewheel 450 airframe, E600 motors with 12-inch propellers and 3DR Pixhawk autopilot – is capable of achieving the required flight speed of 20 m/s while carrying high-definition onboard cameras and other sensors, such as LIDAR, sonar and inertial measurement units. During the testing, researchers also demonstrated initial autonomous capabilities, such as seeing obstacles and flying around them at a slow speed while unaided by a human controller.

“We’re excited that we were able to validate the airspeed goal during this first flight data collection,” says Mark Micire, DARPA’s program manager. “The fact that some teams also demonstrated basic autonomous flight ahead of schedule was an added bonus. The challenge for the teams now is to advance the algorithms and onboard computational efficiency to extend the UAVs’ perception range and compensate for the vehicles’ mass to make extremely tight turns and abrupt maneuvers at high speeds.”

The three performer teams are Draper, teamed with the Massachusetts Institute of Technology; the University of Pennsylvania; and Scientific Systems Co. Inc., teamed with AeroVironment.

The test flight and data collection took place at Otis Air National Guard Base in Cape Cod, Mass., in a former aircraft hangar that was transformed into a warehouse setting with simulated walls, boxes and other obstacles to test flight agility and speed.

However, the test run also resulted in several crashes.

“But the only way to achieve hard goals is to push physical systems and software to the limit,” Micire explains. “I expect there will be more flight failures and smashed quadcopters along the way.”

With each successive program milestone flight test, the warehouse venue will be made more complicated by adding obstacles and clutter to create a more challenging and realistic environment for the UAVs to navigate autonomously, says DARPA.

“Very lightweight UAVs exist today that are agile and can fly faster than 20 meters per second, but they can’t carry the sensors and computation to fly autonomously in cluttered environments,” Micire continues. “And large UAVs exist that can fly high and fast with heavy computing payloads and sensors on board. What makes the FLA program so challenging is finding the sweet spot of a small size, weight and power air vehicle with limited onboard computing power to perform a complex mission completely autonomously.”

DARPA says the FLA program’s initial focus is on UAVs, but advances made through the program could potentially be applied to ground, marine and underwater systems, which could be especially useful in GPS-degraded or denied environments.

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