CNN Uses Vantage Robotics' Snap Drone to Win FAA Fly-Over-People Waiver

The news network is now allowed to film over crowds using a lightweight video drone

3 min read
Vantage Robotics' Snap drone weighs just 620 grams and is held together with magnets, allowing it to come apart on impact.
Vantage Robotics' Snap drone weighs just 620 grams and is held together with magnets, allowing it to come apart on impact.
Image: Vantage Robotics

The U.S. Federal Aviation Administration’s Small UAS Rule (also known as Part 107) has provisions to obtaining waivers to the usual requirements for flying drones in the United States. For example, you’re not generally allowed to fly drones at night, although the FAA has granted quite a few waivers allowing flight after dark.

But another rule is that you can’t fly drones over people who are not part of your operations, and until about a week ago, the FAA hadn’t waived that rule for anybody. Now it has, for CNN. The FAA is allowing the cable news network to use a drone to obtain video over uninvolved people, even crowds assembled at places like sporting events.

Clearly, the safety of folks beneath the drone was a big concern here. CNN says it was able to address the issue by using a drone called Snap from San Francisco Bay Area startup Vantage Robotics.

Snap drone from Vantage Robotics Most quadcopters control yaw using just the torque that develops in reaction to changes in the speed of the blades. Vantage Robotics decided to make yaw control more responsive by slightly tilting the front propellers backward and the rear propellers forward. This configuration creates thrust forces that apply a torque directly to the frame of the craft. Photo: Vantage Robotics

Snap weighs just 620 grams (1.4 pounds). And it’s held together with magnets, allowing it to come apart on impact—say, with your head—which makes it less likely to do any lasting damage. AeroVironment has been using the same strategy with hand-launched military drones—not so that they don’t do inadvertent collateral damage, but so that they don’t damage themselves during their rather hard deep-stall landings.

Another safety measure Snap includes are shrouds around its whirling blades. That’s not uncommon for drones, particularly those you might fly inside. But Vantage Robotics cleverly designed blade shrouds using “tensegrity,” a term that American inventor Buckminster Fuller coined more than half a century ago, and which refers to objects that use components in compression or tension to maintain their structure. (NASA is also using tensegrity-based designs, to build robots.) A bicycle wheel would be an example of the kind of thing that inspired Snap’s featherweight blade shrouds.

Vantage Robotics' Snap drone Snap has blade shrouds based on a tensegrity structure that is lightweight but strong. Image: Vantage Robotics

Perhaps a greater innovation is the strategy Snap adopted to control yaw—movements that make the drone rotate to the left and right. Other quadcopters control yaw using just the torque that develops in reaction to changes in the speed of the blades. Two diagonally opposed blades are made to speed up, while the other two are made to slow down. The overall upward thrust is the same, but because those pairs rotate in opposite directions, the body of the drone rotates in response.

The problem is that this reaction torque doesn’t have much oomph. So it’s hard to make yaw control very responsive in drones of this type. And that was a particular problem here, because Vantage Robotics didn’t want to have to add a third axis to its camera gimbal to damp out yaw motions. So it needed to have the whole drone yaw on command swiftly and precisely. The company’s solution, according to a patent application filed last year, was to cant the propellers: The two on the front point somewhat backward; the two on the rear point somewhat forward.

Small dihedral angles of this type are often used for the wings of aircraft to add stability. In model airplanes, wing dihedral also allows the plane to bank with just rudder control. Snap’s dihedral improves yaw “authority” because when two diagonally opposed propellers spin up, their canted thrust forces apply a torque directly to the frame of the craft.

My hat’s off to the company for creating what looks to be a very benign yet capable drone. It’ll be fascinating to see what kind of video footage CNN is able to attain with it.

The Conversation (0)

How the U.S. Army Is Turning Robots Into Team Players

Engineers battle the limits of deep learning for battlefield bots

11 min read
Robot with threads near a fallen branch

RoMan, the Army Research Laboratory's robotic manipulator, considers the best way to grasp and move a tree branch at the Adelphi Laboratory Center, in Maryland.

Evan Ackerman

This article is part of our special report on AI, “The Great AI Reckoning.

"I should probably not be standing this close," I think to myself, as the robot slowly approaches a large tree branch on the floor in front of me. It's not the size of the branch that makes me nervous—it's that the robot is operating autonomously, and that while I know what it's supposed to do, I'm not entirely sure what it will do. If everything works the way the roboticists at the U.S. Army Research Laboratory (ARL) in Adelphi, Md., expect, the robot will identify the branch, grasp it, and drag it out of the way. These folks know what they're doing, but I've spent enough time around robots that I take a small step backwards anyway.

The robot, named RoMan, for Robotic Manipulator, is about the size of a large lawn mower, with a tracked base that helps it handle most kinds of terrain. At the front, it has a squat torso equipped with cameras and depth sensors, as well as a pair of arms that were harvested from a prototype disaster-response robot originally developed at NASA's Jet Propulsion Laboratory for a DARPA robotics competition. RoMan's job today is roadway clearing, a multistep task that ARL wants the robot to complete as autonomously as possible. Instead of instructing the robot to grasp specific objects in specific ways and move them to specific places, the operators tell RoMan to "go clear a path." It's then up to the robot to make all the decisions necessary to achieve that objective.

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