2017-02-22: Autonomy Incubator Welcomes Swarm of CICADAs

Danette pulls a Cicada from its crate to show PIs Rania Ghatas, Jim Neilan, and Matt Vaughan.

Four boxes of color-coded CICADA gliders arrived from the Naval Research Laboratory before lunch today, and we were all as excited as you'd expect someone who just received 150 tiny flying robots in the mail to be.

Kyle McQuarry with a fresh-from-the-box yellow CICADA.

These little guys will be dropped en masse from the Hive to gather atmospheric data on the upcoming OWLETS mission. Essentially, the Hive will carry them high into the air at the beginning of the route and release all 150 of them at the designated altitude, and then the CICADAs will autonomously navigate to the end point, collecting air quality data the whole way there.

Before that happens, though, we have to make sure they're all flight-ready and fully functional. That duty falls to PI Matt Vaughan.

"I'm checking to make sure that the GPS is working, that it powers on, that it knows right from left," he said. "We also need to check their pairing mechanism, where if you stack them they go into armed-for-flight mode."

Stacked and armed CICADAs.

One of the coolest features about the CICADA is the way they preserve battery life: they don't arm for flight until they're stacked in pairs, when magnets on the front and back ends of each vehicle align. Once they're armed, they don't switch on and start navigating until they're unpaired by the force of free-falling.

"When they separate from each other as they fall and tumble, they'll realize, 'Oh, I'm falling because I'm not paired anymore,' and then they'll enter spin recovery mode, get a GPS fix, and start gliding towards where the waypoint is," Matt explained.

Separated and ready-to-glide CICADAs.

Once the CICADA reaches its GPS waypoint, it enters a spiral pattern around the point until it hits the ground. All of the navigation happens onboard via a GPS sensor and two servos to adjust the wing flaps; communication with the ground station only involves streaming data and status updates of the sensors.

Ben is actually holding the CICADA right side-up—
they fly with the bulk of their bodies underneath them.

Before we can start dropping CICADAs anywhere, however, Matt must overcome one more logistical hurdle.

"I have to charge all of them," he said. "I need a lot of cables and a lot of chargers."

Note: If you're interested in reading more about CICADAs, here's a NRL press release, an article from AFCEA that I found helpful, and here's an AIAA conference paper from NRL explaining the design evolution. 

2017-02-09: Autonomy Incubator Collaborates with MIT on Collaborative Search-And-Rescue Vehicles

Loc hand-flies the UAV through the search area.

As part of the collaboration between NASA Langley's DELIVER initiative and MIT's SRTC (Search and Rescue under The Canopy) project, Ai engineer Loc Tran has spent the last two days tromping through the woods in the back half of the center, a UAV held at arm's length in front of him.

"We're recording data," he said before handing me a laptop. He took the UAV on long, looping paths through the forest, while I followed behind him and watched streams of data flow in from the onboard sensors– GPS positioning information, measurements from the lidar on top of the UAV, video from the front-mounted camera. Everything the UAV would need to fly autonomously was already on board; I was just there to monitor that it was working. Houston to the Apollo 11, if you will.

My view from Mission Control.

"So, it's making maps right now?" I asked, as we passed the same bench for the third time.

"Yeah, but what's important is that we're going through the same area in different directions to match up the maps we get," Loc explained.

UAVs have had the ability to navigate and create maps for years now; look at all the PTAM and computer vision research we've already done at the Ai. This UAV is unique in that as it navigates and creates maps, it shares those maps with other vehicles navigating the same area to collaboratively create one big master map. By looping around and crossing through the search area multiple times, Loc can test the map-matching algorithm to verify that it recognizes the same topography from different angles.

"We want to be able to know where one drone has searched versus where another drone has searched," he said. In a search-and-rescue situation, time is a precious commodity. If the team of search vehicles can collaborate in their analysis instead of individually scanning for the same subject, the time saved could be crucial to a successful rescue.

The modern, less cuddly version of a Swiss Saint Bernard.

Once we made enough laps around the search area, Loc took the equipment back to the Ai and prepared the data to send off to MIT.

"This is their design; we're helping them with the operations aspect of it– testing the thing, collecting data and trying [the algorithm] on our own data set," he said. "They don't have woods where they are." Critical in an under-the-canopy search project.

Before the day was over, Loc also switched places with me so I could take the UAV for a joyride. Hand-flying is harder than it looks– the lidar has a 270° field of vision so you have to stay right behind the vehicle to keep out of the way, plus it's heavy– but the information I collected will become part of the project data set. You're welcome, America!

Me, proving that English majors really can do anything.

2017-02-08: Autonomy Incubator Transforms PIs into Pilots

In pursuit of greater efficiency and a deeper understanding of unmanned flight, three intrepid Ai members– Jim Neilan, Ben Kelley, and Matt Vaughan– have volunteered to become UAV pilots. This month marked the beginning of their training under the guidance of Zak Johns, our resident UAV pilot. With more people available to serve as safety pilots during flight tests, we're looking forward to faster turnarounds and decreased demand on Zak as the only (but still best!) pilot around.

"Zak has been a scarce resource," Ben explained. "Whenever we need a safety pilot, we're all competing for his time and his effort, and he has other jobs to do... whenever repairs need to be made or new builds or things like that, Zak's the one who gets tasked with those."

Kyle McQuarry, Matt, and Ben learn how to break down the Hive.

The first day of the introductory course was entirely classroom-based to cover every aspect of UAV assembly and maintenance, from how to check if a motor needs to be replaced– twist it in your fingers and "feel the cogging," Zak says– to the correct way to charge a lithium-polymer battery. Sayer Fisher, lead engineer of the Hive (and former Ai intern!), demonstrated how to take the vehicle from storage position to flight readiness.

Sayer locks one of the Hive's arms in place with screws.

Ralph and Jim examine a prop during class.

After the classroom intensive, the next day focused on hands-on flight instruction. Zak started Jim, Ben, and Matt on small quadrotors to let them get used to the controls, then worked them up to flying the big research vehicles like the Orevkon quadrotor or the Hive by the end of the afternoon.

Danette and Zak co-pilot.

Ben gets into the flight range to train with Zak's large hexrotor.

Jim flies the Hive.