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#436263 Skydio 2 Review: This Is the Drone You ...
Let me begin this review by saying that the Skydio 2 is one of the most impressive robots that I have ever seen. Over the last decade, I’ve spent enough time around robots to have a very good sense of what kinds of things are particularly challenging for them, and to set my expectations accordingly. Those expectations include things like “unstructured environments are basically impossible” and “full autonomy is impractically expensive” and “robot videos rarely reflect reality.”
Skydio’s newest drone is an exception to all of this. It’s able to fly autonomously at speed through complex environments in challenging real-world conditions in a way that’s completely effortless and stress-free for the end user, allowing you to capture the kind of video that would be otherwise impossible, even (I’m guessing) for professional drone pilots. When you see this technology in action, it’s (almost) indistinguishable from magic.
Skydio 2 Price
To be clear, the Skydio 2 is not without compromises, and the price of $999 (on pre-order with delivery of the next batch expected in spring of 2020) requires some justification. But the week I’ve had with this drone has left me feeling like its fundamental autonomous capability is so far beyond just about anything that I’ve ever experienced that I’m questioning why I would every fly anything else ever again.
We’ve written extensively about Skydio, beginning in early 2016 when the company posted a video of a prototype drone dodging trees while following a dude on a bike. Even three years ago, Skydio’s tech was way better than anything we’d seen outside of a research lab, and in early 2018, they introduced their first consumer product, the Skydio R1. A little over a year later, Skydio has introduced the Skydio 2, which is smaller, smarter, and much more affordable. Here’s an overview video just to get you caught up:
Skydio sent me a Skydio 2 review unit last week, and while I’m reasonably experienced with drones in general, this is the first time I’ve tried a Skydio drone in person. I had a pretty good idea what to expect, and I was absolutely blown away. Like, I was giggling to myself while running through the woods as the drone zoomed around, deftly avoiding trees and keeping me in sight. Robots aren’t supposed to be this good.
A week is really not enough time to explore everything that the Skydio can do, especially Thanksgiving week in Washington, D.C. (a no-fly zone) in early winter. But I found a nearby state park in which I could legally and safely fly the drone, and I did my best to put the Skydio 2 through its paces.
Note: Throughout this review, we’ve got a bunch of GIFs to help illustrate different features of the drone. To fit them all in, these GIFs had to be heavily compressed. Underneath each GIF is a timestamped link to this YouTube video (also available at the bottom of the post), which you can click on to see the an extended cut of the original 4K 30 fps footage. And there’s a bunch of interesting extra video in there as well.
Skydio 2 Specs
Photo: Evan Ackerman/IEEE Spectrum
The Skydio 2 is primarily made out of magnesium, which (while light) is both heavier and more rigid and durable than plastic. The offset props (the back pair are above the body, and the front pair are below) are necessary to maintain the field of view of the navigation cameras.
The Skydio 2 both looks and feels like a well-designed and carefully thought-out drone. It’s solid, and a little on the heavy side as far as drones go—it’s primarily made out of magnesium, which (while light) is both heavier and more rigid and durable than plastic. The blue and black color scheme is far more attractive than you typically see with drones.
Photo: Evan Ackerman/IEEE Spectrum
To detect and avoid obstacles, the Skydio 2 uses an array of six 4K hemispherical cameras that feed data into an NVIDIA Jetson TX2 at 30 fps, with the drone processing a million points in 3D space per second to plan the safest path.
The Skydio 2 is built around an array of six hemispherical obstacle-avoidance cameras and the NVIDIA Jetson TX2 computing module that they’re connected to. This defines the placement of the gimbal, the motors and props, and the battery, since all of this stuff has to be as much as possible out of the view of the cameras in order for the drone to effectively avoid obstacles in any direction.
Without the bottom-mounted battery attached, the drone is quite flat. The offset props (the back pair are above the body, and the front pair are below) are necessary to maintain the field of view of the obstacle-avoidance cameras. These hemispherical cameras are on the end of each of the prop arms as well as above and below the body of the drone. They look awfully exposed, even though each is protected from ground contact by a little fin. You need to make sure these cameras are clean and smudge-free, and Skydio includes a cleaning cloth for this purpose. Underneath the drone there are slots for microSD cards, one for recording from the camera and a second one that the drone uses to store data. The attention to detail extends to the SD card insertion, which has a sloped channel that guides the card securely into its slot.
Once you snap the battery in, the drone goes from looking streamlined to looking a little chubby. Relative to other drones, the battery almost seems like an afterthought, like Skydio designed the drone and then remembered, “oops we have to add a battery somewhere, let’s just kludge it onto the bottom.” But again, the reason for this is to leave room inside the body for the NVIDIA TX2, while making sure that the battery stays out of view of the obstacle avoidance cameras.
The magnetic latching system for the battery is both solid and satisfying. I’m not sure why it’s necessary, strictly speaking, but I do like it, and it doesn’t seem like the battery will fly off even during the most aggressive maneuvers. Each battery includes an LED array that will display its charge level in 25 percent increments, as well as a button that you push to turn the drone on and off. Charging takes place via a USB-C port in the top of the drone, which I don’t like, because it means that the batteries can’t be charged on their own (like the Parrot Anafi’s battery), and that you can’t charge one battery while flying with another, like basically every other drone ever. A separate battery charger that will charge two at once is available from Skydio for an eyebrow-raising $129.
I appreciate that all of Skydio’s stuff (batteries, controller, and beacon) charges via USB-C, though. The included USB-C adapter with its beefy cable will output at up to 65 watts, which’ll charge a mostly depleted battery in under an hour. The drone turns itself on while charging, which seems unnecessary.
Photo: Evan Ackerman/IEEE Spectrum
The Skydio 2 is not foldable, making it not nearly as easy to transport as some other drones. But it does come with a nice case that mitigates this issue somewhat, and the drone plus two batteries end up as a passably flat package about the size of a laptop case.
The most obvious compromise that Skydio made with the Skydio 2 is that the drone is not foldable. Skydio CEO Adam Bry told us that adding folding joints to the arms of the Skydio 2 would have made calibrating all six cameras a nightmare and significantly impacted performance. This makes complete sense, of course, but it does mean that the Skydio 2 is not nearly as easy to transport as some other drones.
Photo: Evan Ackerman/IEEE Spectrum
Folded and unfolded: The Skydio 2 compared to the Parrot Anafi (upper left) and the DJI Mavic Pro (upper right).
The Skydio 2 does come with a very nice case that mitigates this issue somewhat, and the drone plus two batteries end up as a passably flat package about the size of a laptop case. Still, it’s just not as convenient to toss into a backpack as my Anafi, although the Mavic Mini might be even more portable.
Photo: Evan Ackerman/IEEE Spectrum
While the Skydio 2’s case is relatively compact, the non-foldable drone is overall a significantly larger package than the Parrot Anafi.
The design of the drone leads to some other compromises as well. Since landing gear would, I assume, occlude the camera system, the drone lands directly on the bottom of its battery pack, which has a slightly rubberized pad about the size of a playing card. This does’t feel particularly stable unless you end up on a very flat surface, and made me concerned for the exposed cameras underneath the drone as well as the lower set of props. I’d recommend hand takeoffs and landings—more on those later.
Skydio 2 Camera System
Photo: Evan Ackerman/IEEE Spectrum
The Skydio 2’s primary camera is a Sony IMX577 1/2.3″ 12.3-megapixel CMOS sensor. It’s mounted to a three-axis gimbal and records 4K video at 60 fps, or 1080p video at 120 fps.
The Skydio 2 comes with a three-axis gimbal supporting a 12-megapixel camera, just enough to record 4K video at 60 fps, or 1080p video at 120 fps. Skydio has provided plenty of evidence that its imaging system is at least as good if not better than other drone cameras. Tested against my Mavic Pro and Parrot Anafi, I found no reason to doubt that. To be clear, I didn’t do exhaustive pixel-peeping comparisons between them, you’re just getting my subjective opinion that the Skydio 2 has a totally decent camera that you won’t be disappointed with. I will say that I found the HDR photo function to be not all that great under the few situations in which I tested it—after looking at a few muddy sunset shots, I turned it off and was much happier.
Photo: Evan Ackerman/IEEE Spectrum
The Skydio 2’s 12-megapixel camera is solid, although we weren’t impressed with the HDR option.
The video stabilization is fantastic, to the point where watching the video footage can be underwhelming because it doesn’t reflect the motion of the drone. I almost wish there was a way to change to unstabilized (or less-stabilized) video so that the viewer could get a little more of a wild ride. Or, ideally, there’d be a way for the drone to provide you with a visualization of what it was doing using the data collected by its cameras. That’s probably wishful thinking, though. The drone itself doesn’t record audio because all you’d get would be an annoying buzz, but the app does record audio, so the audio from your phone gets combined with the drone video. Don’t expect great quality, but it’s better than nothing.
Skydio 2 App
The app is very simple compared to every other drone app I’ve tried, and that’s a good thing. Here’s what it looks like:
Image: Skydio
Trackable subjects get a blue “+” sign over them, and if you tap them, the “+” turns into a spinny blue circle. Once you’ve got a subject selected, you can choose from a variety of cinematic skills that the drone will execute while following you.
You get the controls that you need and the information that you need, and nothing else. Manual flight with the on-screen buttons works adequately, and the double-tap to fly function on the phone works surprisingly well, making it easy to direct the drone to a particular spot above the ground.
The settings menus are limited but functional, allowing you to change settings for the camera and a few basic tweaks for controlling the drone. One unique setting to the Skydio 2 is the height floor—since the drone only avoids static obstacles, you can set it to maintain a height of at least 8 feet above the ground while flying autonomously to make sure that if you’re flying around other people, it won’t run into anyone who isn’t absurdly tall and therefore asking for it.
Trackable subjects get a blue “+” sign over them in the app, and if you tap them, the “+” turns into a spinny blue circle. Once you’ve got a subject selected, you can choose from a variety of cinematic skills that the drone will execute while following you, and in addition, you can select “one-shot” skills that involve the drone performing a specific maneuver before returning to the previously selected cinematic skill. For example, you can tell the drone to orbit around you, and then do a “rocket” one-shot where it’ll fly straight up above you (recording the whole time, of course), before returning to its orbiting.
After you’re done flying, you can scroll through your videos and easily clip out excerpts from them and save them to your phone for sharing. Again, it’s a fairly simple interface without a lot of options. You could call it limited, I guess, but I appreciate that it just does a few things that you care about and otherwise doesn’t clutter itself up.
The real limitation of the app is that it uses Wi-Fi to connect to the Skydio 2, which restricts the range. To fly much beyond a hundred meters or so, you’ll need to use the controller or beacon instead.
Skydio 2 Controller and Beacon
Photo: Evan Ackerman/IEEE Spectrum
While the Skydio 2 controller provides a better hands-on flight experience than with the phone, plus an extended range of up to 3.5 km, more experienced pilots may find manual control a bit frustrating, because the underlying autonomy will supersede your maneuvers when you start getting close to objects.
I was looking forward to using the controller, because with every other drone I’ve had, the precision that a physically controller provides is, I find, mandatory for a good flying experience and to get the photos and videos that you want. With Skydio 2, that’s all out the window. It’s not that the controller is useless or anything, it’s just that because the drone tracks you and avoids obstacles on its own, that level of control precision becomes largely unnecessary.
The controller itself is perfectly fine. It’s a rebranded Parrot Skycontroller3, which is the same as the one that you get with a Parrot Anafi. It’s too bad that the sticks don’t unscrew to make it a little more portable, and overall it’s functional rather than fancy, but it feels good to use and includes a sizeable antenna that makes a significant difference to the range that you get (up to 3.5 kilometers).
You definitely get a better hands-on flight experience with the controller than with the phone, so if you want to (say) zip the drone around some big open space for fun, it’s good for that. And it’s nice to be able to hand the controller to someone who’s never flown a drone before and let them take it for a spin without freaking out about them crashing it the whole time. For more experienced pilots, though, the controller is ultimately just a bit frustrating, because the underlying autonomy will supersede your control when you start getting close to objects, which (again) limits how useful the controller is relative to your phone.
I do still prefer the controller over the phone, but I’m not sure that it’s worth the extra $150, unless you plan to fly the Skydio 2 at very long distances or primarily in manual mode. And honestly, if either of those two things are your top priority, the Skydio 2 is probably not the drone for you.
Photo: Evan Ackerman/IEEE Spectrum
The Skydio 2 beacon uses GPS tracking to help the drone follow you, extending range up to 1.5 km. You can also fly the with the beacon alone, no phone necessary.
The purpose of the beacon, according to Skydio, is to give the drone a way of tracking you if it can’t see you, which can happen, albeit infrequently. My initial impression of the beacon was that it was primarily useful as a range-extending bridge between my phone and the drone. But I accidentally left my phone at home one day (oops) and had to fly the drone with only the beacon, and it was a surprisingly decent experience. The beacon allows for full manual control of a sort—you can tap different buttons to rotate, fly forward, and ascend or descend. This is sufficient for takeoff, landing, to make sure that the drone is looking at you when you engage visual tracking, and to rescue it if it gets trapped somewhere.
The rest of the beacon’s control functions are centered around a few different tracking modes, and with these, it works just about as well as your phone. You have fewer options overall, but all the basic stuff is there with just a few intuitive button clicks, including tracking range and angle. If you’re willing to deal with this relatively minor compromise, it’s nice to not have your phone available for other things rather than being monopolized by the drone.
Skydio 2 In Flight
GIF: Evan Ackerman/IEEE Spectrum
Hand takeoffs are simple and reliable.
Click here for a full resolution clip.
Starting up the Skydio 2 doesn’t require any kind of unusual calibration steps or anything like that. It prefers to be kept still, but you can start it up while holding it, it’ll just take a few seconds longer to tell you that it’s ready to go. While the drone will launch from any flat surface with significant clearance around it (it’ll tell you if it needs more room), the small footprint of the battery means that I was more comfortable hand launching it. This is not a “throw” launch; you just let the drone rest on your palm, tell it to take off, and then stay still while it gets its motors going and then gently lifts off. The lift off is so gentle that you have to be careful not to pull your hand away too soon—I did that once and the drone, being not quite ready, dropped towards the ground, but managed to recover without much drama.
GIF: Evan Ackerman/IEEE Spectrum
Hand landings always look scary, but the Skydio 2 is incredibly gentle. After trying this once, it became the only way I ever landed the drone.
Click here for a full resolution clip.
Catching the drone for landing is perhaps very slightly more dangerous, but not any more difficult. You put the drone above and in front of you facing away, tell it to land in the app or with the beacon, and then put your hand underneath it to grasp it as it slowly descends. It settles delicately and promptly turns itself off. Every drone should land this way. The battery pack provides a good place to grip, although you do have to be mindful of the forward set of props, which (since they’re the pair that are beneath the body of drone) are quite close to your fingers. You’ll certainly be mindful after you catch a blade with your fingers once. Which I did. For the purposes of this review and totally not by accident. No damage, for the record.
Photo: Evan Ackerman/IEEE Spectrum
You won’t be disappointed with the Skydio 2’s in-flight performance, unless you’re looking for a dedicated racing drone.
In normal flight, the Skydio 2 performs as well as you’d expect. It’s stable and manages light to moderate wind without any problems, although I did notice some occasional lateral drifting when the drone should have been in a stationary hover. While the controller gains are adjustable, the Skydio 2 isn’t quite as aggressive in flight as my Mavic Pro on Sport Mode, but again, if you’re looking for a high-speed drone, that’s really not what the Skydio is all about.
The Skydio 2 is substantially louder than my Anafi, although the Anafi is notably quiet for a drone. It’s not annoying to hear (not a high-pitched whine), but you can hear it from a ways away, and farther away than my Mavic Pro. I’m not sure whether that’s because of the absolute volume or the volume plus the pitch. In some ways, this is a feature, since you can hear the drone following you even if you’re not looking at it, you just need to be aware of the noise it makes when you’re flying it around people.
Obstacle Avoidance
The primary reason Skydio 2 is the drone that you want to fly is because of its autonomous subject tracking and obstacle avoidance. Skydio’s PR videos make this capability look almost too good, and since I hadn’t tried out one of their drones before, the first thing I did with it was exactly what you’d expect: attempt to fly it directly into the nearest tree.
GIF: Evan Ackerman/IEEE Spectrum
The Skydio 2 deftly slides around trees and branches. The control inputs here were simple “forward” or “turn,” all obstacle avoidance is autonomous.
Click here for a full resolution clip.
And it just won’t do it. It slows down a bit, and then slides right around one tree after another, going over and under and around branches. I pointed the drone into a forest and just held down “forward” and away it went, without any fuss, effortlessly ducking and weaving its way around. Of course, it wasn’t effortless at all—six 4K cameras were feeding data into the NVIDIA TX2 at 30 fps, and the drone was processing a million points in 3D space per second to plan the safest path while simultaneously taking into account where I wanted it to go. I spent about 10 more minutes doing my level best to crash the drone into anything at all using a flying technique probably best described as “reckless,” but the drone was utterly unfazed. It’s incredible.
What knocked my socks off was telling the drone to pass through treetops—in the clip below, I’m just telling the drone to fly straight down. Watch as it weaves its way through gaps between the branches:
GIF: Evan Ackerman/IEEE Spectrum
The result of parking the Skydio 2 above some trees and holding “down” on the controller is this impressive fully autonomous descent through the branches.
Click here for a full resolution clip.
Here’s one more example, where I sent the drone across a lake and started poking around in a tree. Sometimes the Skydio 2 isn’t sure where you want it to go, and you have to give it a little bit of a nudge in a clear direction, but that’s it.
GIF: Evan Ackerman/IEEE Spectrum
In obstacle-heavy environments, the Skydio 2 prudently slows down, but it can pick its way through almost anything that it can see.
Click here for a full resolution clip.
It’s important to keep in mind that all of the Skydio 2’s intelligence is based on vision. It uses cameras to see the world, which means that it has similar challenges as your eyes do. Specifically, Skydio warns against flying in the following conditions:
Skydio 2 can’t see certain visually challenging obstacles. Do not fly around thin branches, telephone or power lines, ropes, netting, wires, chain link fencing or other objects less than ½ inch in diameter.
Do not fly around transparent surfaces like windows or reflective surfaces like mirrors greater than 60 cm wide.
When the sun is low on the horizon, it can temporarily blind Skydio 2’s cameras depending on the angle of flight. Your drone may be cautious or jerky when flying directly toward the sun.
Basically, if you’d have trouble seeing a thing, or seeing under some specific flight conditions, then the Skydio 2 almost certainly will also. It gets even more problematic when challenging obstacles are combined with challenging flight conditions, which is what I’m pretty sure led to the only near-crash I had with the drone. Here’s a video:
GIF: Evan Ackerman/IEEE Spectrum
Flying around very thin branches and into the sun can cause problems for the Skydio 2’s obstacle avoidance.
Click here for a full resolution clip.
I had the Skydio 2 set to follow me on my bike (more about following and tracking in a bit). It was mid afternoon, but since it’s late fall here in Washington, D.C., the sun doesn’t get much higher than 30 degrees above the horizon. Late fall also means that most of the deciduous trees have lost their leaves, and so there are a bunch of skinny branches all over the place. The drone was doing a pretty good job of following me along the road at a relatively slow speed, and then it clipped the branch that you can just barely see in the video above. It recovered in an acrobatic maneuver that has been mostly video-stabilized out, and resumed tracking me before I freaked and told it to land. You can see another example here, where the drone (again) clips a branch that has the sun behind it, and this clip shows me stopping my bike before the drone runs into another branch in a similar orientation. As the video shows, it’s very hard to see the branches until it’s too late.
As far as I can tell, the drone is no worse for wear from any of this, apart from a small nick in one of the props. But, this is a good illustration of a problematic situation for the Skydio 2: flying into a low sun angle around small bare branches. Should I not have been flying the drone in this situation? It’s hard to say. These probably qualify as “thin branches,” although there was plenty of room along with middle of the road. There is an open question with the Skydio 2 as to exactly how much responsibility the user should have about when and where it’s safe to fly—for branches, how thin is too thin? How low can the sun be? What if the branches are only kinda thin and the sun is only kinda low, but it’s also a little windy? Better to be safe than sorry, of course, but there’s really no way for the user (or the drone) to know what it can’t handle until it can’t handle it.
Edge cases like these aside, the obstacle avoidance just works. Even if you’re not deliberately trying to fly into branches, it’s keeping a lookout for you all the time, which means that flying the drone goes from somewhat stressful to just pure fun. I can’t emphasize enough how amazing it is to be able to fly without worrying about running into things, and how great it feels to be able to hand the controller to someone who’s never flown a drone before and say, with complete confidence, “go ahead, fly it around!”
Skydio 2 vs. DJI Mavic
Photo: Evan Ackerman/IEEE Spectrum
Both the Skydio 2 and many models of DJI’s Mavic use visual obstacle avoidance, but the Skydio 2 is so much more advanced that you can’t really compare the two systems.
It’s important to note that there’s a huge difference between the sort of obstacle avoidance that you get with a DJI Mavic, and the sort of obstacle avoidance that you get with the Skydio 2. The objective of the Mavic’s obstacle avoidance is really there to prevent you from accidentally running into things, and in that capacity, it usually works. But there are two things to keep in mind here—first, not running into things is not the same as avoiding things, because avoiding things means planning several steps ahead, not just one step.
Second, there’s the fact that the Mavic’s obstacle detection only works most of the time. Fundamentally, I don’t trust my Mavic Pro, because sometimes the safety system doesn’t kick in for whatever reason and the drone ends up alarmingly close to something. And that’s actually fine, because with the Mavic, I expect to be piloting it. It’s for this same reason that I don’t care that my Parrot Anafi doesn’t have obstacle avoidance at all: I’m piloting it anyway, and I’m a careful pilot, so it just doesn’t matter. The Skydio 2 is totally and completely different. It’s in a class by itself, and you can’t compare what it can do to what anything else out there right now. Period.
Skydio 2 Tracking
Skydio’s big selling point on the Skydio 2 is that it’ll autonomously track you while avoiding obstacles. It does this visually, by watching where you go, predicting your future motion, and then planning its own motion to keep you in frame. The works better than you might expect, in that it’s really very good at not losing you. Obviously, the drone prioritizes not running into stuff over tracking you, which means that it may not always be where you feel like it should be. It’s probably trying to get there, but in obstacle dense environments, it can take some creative paths.
Having said that, I found it to be very consistent with keeping me in the frame, and I only managed to lose it when changing direction while fully occluded by an obstacle, or while it was executing an avoidance maneuver that was more dynamic than normal. If you deliberately try to hide from the drone it’s not that hard to do so if there are enough obstacles around, but I didn’t find the tracking to be something that I had to worry about it most cases. When tracking does fail and you’re not using the beacon, the drone will come to a hover. It won’t try and find you, but it will reacquire you if you get back into its field of view.
The Skydio 2 had no problem tracking me running through fairly dense trees:
GIF: Evan Ackerman/IEEE Spectrum
The Skydio 2 had no problem chasing me around through these trees, even while I was asking it to continually change its tracking angle.
Click here for a full resolution clip.
It also managed to keep up with me as I rode my bike along a tree-lined road:
GIF: Evan Ackerman/IEEE Spectrum
The Skydio 2 is easily fast enough to keep up with me on a bike, even while avoiding tree branches.
Click here for a full resolution clip.
It lost me when I asked it to follow very close behind me as I wove through some particularly branch-y trees, but it fails more or less gracefully by just sort of nope-ing out of situations when they start to get bad and coming to a hover somewhere safe.
GIF: Evan Ackerman/IEEE Spectrum
The Skydio 2 knows better than to put itself into situations that it can’t handle, and will bail to a safe spot if things get too complicated.
Click here for a full resolution clip.
After a few days of playing with the drone, I started to get to the point where I could set it to track me and then just forget about it while I rode my bike or whatever, as opposed to constantly turning around to make sure it was still behind me, which is what I was doing initially. It’s a level of trust that I don’t think would be possible with any other drone.
Should You Buy a Skydio 2?
Photo: Evan Ackerman/IEEE Spectrum
We think the Skydio 2 is fun and relaxing to fly, with unique autonomous intelligence that makes it worth the cost.
In case I haven’t said it often enough in this review, the Skydio 2 is an incredible piece of technology. As far as I know (as a robotics journalist, mind you), this represents the state of the art in commercial drone autonomy, and quite possibly the state of the art in drone autonomy, period. And it’s available for $999, which is expensive, but less money than a Mavic Pro 2. If you’re interested in a new drone, you should absolutely consider the Skydio 2.
There are some things to keep in mind—battery life is a solid but not stellar 20 minutes. Extra batteries are expensive at $99 each (the base kit includes just one). The controller and the beacon are also expensive, at $150 each. And while I think the Skydio 2 is definitely the drone you want to fly, it may not be the drone you want to travel with, since it’s bulky compared to other options.
But there’s no denying the fact that the experience is uniquely magical. Once you’ve flown the Skydio 2, you won’t want to fly anything else. This drone makes it possible to get pictures and videos that would be otherwise impossible, and you can do it completely on your own. You can trust the drone to do what it promises, as long as you’re mindful of some basic and common sense safety guidelines. And we’ve been told that the drone is only going to get smarter and more capable over time.
If you buy a Skydio 2, it comes with the following warranty from Skydio:
“If you’re operating your Skydio 2 within our Safe Flight guidelines, and it crashes, we’ll repair or replace it for free.”
Skydio trusts their drone to go out into a chaotic and unstructured world and dodge just about anything that comes its way. And after a week with this drone, I can see how they’re able to offer this kind of guarantee. This is the kind of autonomy that robots have been promising for years, and the Skydio 2 makes it real.
Detailed technical specifications are available on Skydio’s website, and if you have any questions, post a comment—we’ve got this drone for a little while longer, and I’d be happy to try out (nearly) anything with it.
Skydio 2 Review Video Highlights
This video is about 7 minutes of 4K, 30 fps footage directly from the Skydio 2. The only editing I did was cutting clips together, no stabilization or color correcting or anything like that. The drone will record in 4K 60 fps, so it gets smoother than this, but I, er, forgot to change the setting.
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#436220 How Boston Dynamics Is Redefining Robot ...
Gif: Bob O’Connor/IEEE Spectrum
With their jaw-dropping agility and animal-like reflexes, Boston Dynamics’ bioinspired robots have always seemed to have no equal. But that preeminence hasn’t stopped the company from pushing its technology to new heights, sometimes literally. Its latest crop of legged machines can trudge up and down hills, clamber over obstacles, and even leap into the air like a gymnast. There’s no denying their appeal: Every time Boston Dynamics uploads a new video to YouTube, it quickly racks up millions of views. These are probably the first robots you could call Internet stars.
Spot
Photo: Bob O’Connor
84 cm HEIGHT
25 kg WEIGHT
5.76 km/h SPEED
SENSING: Stereo cameras, inertial measurement unit, position/force sensors
ACTUATION: 12 DC motors
POWER: Battery (90 minutes per charge)
Boston Dynamics, once owned by Google’s parent company, Alphabet, and now by the Japanese conglomerate SoftBank, has long been secretive about its designs. Few publications have been granted access to its Waltham, Mass., headquarters, near Boston. But one morning this past August, IEEE Spectrum got in. We were given permission to do a unique kind of photo shoot that day. We set out to capture the company’s robots in action—running, climbing, jumping—by using high-speed cameras coupled with powerful strobes. The results you see on this page: freeze-frames of pure robotic agility.
We also used the photos to create interactive views, which you can explore online on our Robots Guide. These interactives let you spin the robots 360 degrees, or make them walk and jump on your screen.
Boston Dynamics has amassed a minizoo of robotic beasts over the years, with names like BigDog, SandFlea, and WildCat. When we visited, we focused on the two most advanced machines the company has ever built: Spot, a nimble quadruped, and Atlas, an adult-size humanoid.
Spot can navigate almost any kind of terrain while sensing its environment. Boston Dynamics recently made it available for lease, with plans to manufacture something like a thousand units per year. It envisions Spot, or even packs of them, inspecting industrial sites, carrying out hazmat missions, and delivering packages. And its YouTube fame has not gone unnoticed: Even entertainment is a possibility, with Cirque du Soleil auditioning Spot as a potential new troupe member.
“It’s really a milestone for us going from robots that work in the lab to these that are hardened for work out in the field,” Boston Dynamics CEO Marc Raibert says in an interview.
Atlas
Photo: Bob O’Connor
150 cm HEIGHT
80 kg WEIGHT
5.4 km/h SPEED
SENSING: Lidar and stereo vision
ACTUATION: 28 hydraulic actuators
POWER: Battery
Our other photographic subject, Atlas, is Boston Dynamics’ biggest celebrity. This 150-centimeter-tall (4-foot-11-inch-tall) humanoid is capable of impressive athletic feats. Its actuators are driven by a compact yet powerful hydraulic system that the company engineered from scratch. The unique system gives the 80-kilogram (176-pound) robot the explosive strength needed to perform acrobatic leaps and flips that don’t seem possible for such a large humanoid to do. Atlas has inspired a string of parody videos on YouTube and more than a few jokes about a robot takeover.
While Boston Dynamics excels at making robots, it has yet to prove that it can sell them. Ever since its founding in 1992 as a spin-off from MIT, the company has been an R&D-centric operation, with most of its early funding coming from U.S. military programs. The emphasis on commercialization seems to have intensified after the acquisition by SoftBank, in 2017. SoftBank’s founder and CEO, Masayoshi Son, is known to love robots—and profits.
The launch of Spot is a significant step for Boston Dynamics as it seeks to “productize” its creations. Still, Raibert says his long-term goals have remained the same: He wants to build machines that interact with the world dynamically, just as animals and humans do. Has anything changed at all? Yes, one thing, he adds with a grin. In his early career as a roboticist, he used to write papers and count his citations. Now he counts YouTube views.
In the Spotlight
Photo: Bob O’Connor
Boston Dynamics designed Spot as a versatile mobile machine suitable for a variety of applications. The company has not announced how much Spot will cost, saying only that it is being made available to select customers, which will be able to lease the robot. A payload bay lets you add up to 14 kilograms of extra hardware to the robot’s back. One of the accessories that Boston Dynamics plans to offer is a 6-degrees-of-freedom arm, which will allow Spot to grasp objects and open doors.
Super Senses
Photo: Bob O’Connor
Spot’s hardware is almost entirely custom-designed. It includes powerful processing boards for control as well as sensor modules for perception. The sensors are located on the front, rear, and sides of the robot’s body. Each module consists of a pair of stereo cameras, a wide-angle camera, and a texture projector, which enhances 3D sensing in low light. The sensors allow the robot to use the navigation method known as SLAM, or simultaneous localization and mapping, to get around autonomously.
Stepping Up
Photo: Bob O’Connor
In addition to its autonomous behaviors, Spot can also be steered by a remote operator with a game-style controller. But even when in manual mode, the robot still exhibits a high degree of autonomy. If there’s an obstacle ahead, Spot will go around it. If there are stairs, Spot will climb them. The robot goes into these operating modes and then performs the related actions completely on its own, without any input from the operator. To go down a flight of stairs, Spot walks backward, an approach Boston Dynamics says provides greater stability.
Funky Feet
Gif: Bob O’Connor/IEEE Spectrum
Spot’s legs are powered by 12 custom DC motors, each geared down to provide high torque. The robot can walk forward, sideways, and backward, and trot at a top speed of 1.6 meters per second. It can also turn in place. Other gaits include crawling and pacing. In one wildly popular YouTube video, Spot shows off its fancy footwork by dancing to the pop hit “Uptown Funk.”
Robot Blood
Photo: Bob O’Connor
Atlas is powered by a hydraulic system consisting of 28 actuators. These actuators are basically cylinders filled with pressurized fluid that can drive a piston with great force. Their high performance is due in part to custom servo valves that are significantly smaller and lighter than the aerospace models that Boston Dynamics had been using in earlier designs. Though not visible from the outside, the innards of an Atlas are filled with these hydraulic actuators as well as the lines of fluid that connect them. When one of those lines ruptures, Atlas bleeds the hydraulic fluid, which happens to be red.
Next Generation
Gif: Bob O’Connor/IEEE Spectrum
The current version of Atlas is a thorough upgrade of the original model, which was built for the DARPA Robotics Challenge in 2015. The newest robot is lighter and more agile. Boston Dynamics used industrial-grade 3D printers to make key structural parts, giving the robot greater strength-to-weight ratio than earlier designs. The next-gen Atlas can also do something that its predecessor, famously, could not: It can get up after a fall.
Walk This Way
Photo: Bob O’Connor
To control Atlas, an operator provides general steering via a manual controller while the robot uses its stereo cameras and lidar to adjust to changes in the environment. Atlas can also perform certain tasks autonomously. For example, if you add special bar-code-type tags to cardboard boxes, Atlas can pick them up and stack them or place them on shelves.
Biologically Inspired
Photos: Bob O’Connor
Atlas’s control software doesn’t explicitly tell the robot how to move its joints, but rather it employs mathematical models of the underlying physics of the robot’s body and how it interacts with the environment. Atlas relies on its whole body to balance and move. When jumping over an obstacle or doing acrobatic stunts, the robot uses not only its legs but also its upper body, swinging its arms to propel itself just as an athlete would.
This article appears in the December 2019 print issue as “By Leaps and Bounds.” Continue reading →
#436202 Trump CTO Addresses AI, Facial ...
Michael Kratsios, the Chief Technology Officer of the United States, took the stage at Stanford University last week to field questions from Stanford’s Eileen Donahoe and attendees at the 2019 Fall Conference of the Institute for Human-Centered Artificial Intelligence (HAI).
Kratsios, the fourth to hold the U.S. CTO position since its creation by President Barack Obama in 2009, was confirmed in August as President Donald Trump’s first CTO. Before joining the Trump administration, he was chief of staff at investment firm Thiel Capital and chief financial officer of hedge fund Clarium Capital. Donahoe is Executive Director of Stanford’s Global Digital Policy Incubator and served as the first U.S. Ambassador to the United Nations Human Rights Council during the Obama Administration.
The conversation jumped around, hitting on both accomplishments and controversies. Kratsios touted the administration’s success in fixing policy around the use of drones, its memorandum on STEM education, and an increase in funding for basic research in AI—though the magnitude of that increase wasn’t specified. He pointed out that the Trump administration’s AI policy has been a continuation of the policies of the Obama administration, and will continue to build on that foundation. As proof of this, he pointed to Trump’s signing of the American AI Initiative earlier this year. That executive order, Kratsios said, was intended to bring various government agencies together to coordinate their AI efforts and to push the idea that AI is a tool for the American worker. The AI Initiative, he noted, also took into consideration that AI will cause job displacement, and asked private companies to pledge to retrain workers.
The administration, he said, is also looking to remove barriers to AI innovation. In service of that goal, the government will, in the next month or so, release a regulatory guidance memo instructing government agencies about “how they should think about AI technologies,” said Kratsios.
U.S. vs China in AI
A few of the exchanges between Kratsios and Donahoe hit on current hot topics, starting with the tension between the U.S. and China.
Donahoe:
“You talk a lot about unique U.S. ecosystem. In which aspect of AI is the U.S. dominant, and where is China challenging us in dominance?
Kratsios:
“They are challenging us on machine vision. They have more data to work with, given that they have surveillance data.”
Donahoe:
“To what extent would you say the quantity of data collected and available will be a determining factor in AI dominance?”
Kratsios:
“It makes a big difference in the short term. But we do research on how we get over these data humps. There is a future where you don’t need as much data, a lot of federal grants are going to [research in] how you can train models using less data.”
Donahoe turned the conversation to a different tension—that between innovation and values.
Donahoe:
“A lot of conversation yesterday was about the tension between innovation and values, and how do you hold those things together and lead in both realms.”
Kratsios:
“We recognized that the U.S. hadn’t signed on to principles around developing AI. In May, we signed [the Organization for Economic Cooperation and Development Principles on Artificial Intelligence], coming together with other Western democracies to say that these are values that we hold dear.
[Meanwhile,] we have adversaries around the world using AI to surveil people, to suppress human rights. That is why American leadership is so critical: We want to come out with the next great product. And we want our values to underpin the use cases.”
A member of the audience pushed further:
“Maintaining U.S. leadership in AI might have costs in terms of individuals and society. What costs should individuals and society bear to maintain leadership?”
Kratsios:
“I don’t view the world that way. Our companies big and small do not hesitate to talk about the values that underpin their technology. [That is] markedly different from the way our adversaries think. The alternatives are so dire [that we] need to push efforts to bake the values that we hold dear into this technology.”
Facial recognition
And then the conversation turned to the use of AI for facial recognition, an application which (at least for police and other government agencies) was recently banned in San Francisco.
Donahoe:
“Some private sector companies have called for government regulation of facial recognition, and there already are some instances of local governments regulating it. Do you expect federal regulation of facial recognition anytime soon? If not, what ought the parameters be?”
Kratsios:
“A patchwork of regulation of technology is not beneficial for the country. We want to avoid that. Facial recognition has important roles—for example, finding lost or displaced children. There are use cases, but they need to be underpinned by values.”
A member of the audience followed up on that topic, referring to some data presented earlier at the HAI conference on bias in AI:
“Frequently the example of finding missing children is given as the example of why we should not restrict use of facial recognition. But we saw Joy Buolamwini’s presentation on bias in data. I would like to hear your thoughts about how government thinks we should use facial recognition, knowing about this bias.”
Kratsios:
“Fairness, accountability, and robustness are things we want to bake into any technology—not just facial recognition—as we build rules governing use cases.”
Immigration and innovation
A member of the audience brought up the issue of immigration:
“One major pillar of innovation is immigration, does your office advocate for it?”
Kratsios:
“Our office pushes for best and brightest people from around the world to come to work here and study here. There are a few efforts we have made to move towards a more merit-based immigration system, without congressional action. [For example, in] the H1-B visa system, you go through two lotteries. We switched the order of them in order to get more people with advanced degrees through.”
The government’s tech infrastructure
Donahoe brought the conversation around to the tech infrastructure of the government itself:
“We talk about the shiny object, AI, but the 80 percent is the unsexy stuff, at federal and state levels. We don’t have a modern digital infrastructure to enable all the services—like a research cloud. How do we create this digital infrastructure?”
Kratsios:
“I couldn’t agree more; the least partisan issue in Washington is about modernizing IT infrastructure. We spend like $85 billion a year on IT at the federal level, we can certainly do a better job of using those dollars.” Continue reading →
#436094 Agility Robotics Unveils Upgraded Digit ...
Last time we saw Agility Robotics’ Digit biped, it was picking up a box from a Ford delivery van and autonomously dropping it off on a porch, while at the same time managing to not trip over stairs, grass, or small children. As a demo, it was pretty impressive, but of course there’s an enormous gap between making a video of a robot doing a successful autonomous delivery and letting that robot out into the semi-structured world and expecting it to reliably do a good job.
Agility Robotics is aware of this, of course, and over the last six months they’ve been making substantial improvements to Digit to make it more capable and robust. A new video posted today shows what’s new with the latest version of Digit—Digit v2.
We appreciate Agility Robotics foregoing music in the video, which lets us hear exactly what Digit sounds like in operation. The most noticeable changes are in Digit’s feet, torso, and arms, and I was particularly impressed to see Digit reposition the box on the table before grasping it to make sure that it could get a good grip. Otherwise, it’s hard to tell what’s new, so we asked Agility Robotics’ CEO Damion Shelton to get us up to speed.
IEEE Spectrum: Can you summarize the differences between Digit v1 and v2? We’re particularly interested in the new feet.
Damion Shelton: The feet now include a roll degree of freedom, so that Digit can resist lateral forces without needing to side step. This allows Digit v2 to balance on one foot statically, which Digit v1 and Cassie could not do. The larger foot also dramatically decreases load per unit area, for improved performance on very soft surfaces like sand.
The perception stack includes four Intel RealSense cameras used for obstacle detection and pick/place, plus the lidar. In Digit v1, the perception systems were brought up incrementally over time for development purposes. In Digit v2, all perception systems are active from the beginning and tied to a dedicated computer. The perception system is used for a number of additional things beyond manipulation, which we’ll start to show in the next few weeks.
The torso changes are a bit more behind-the-scenes. All of the electronics in it are now fully custom, thermally managed, and environmentally sealed. We’ve also included power and ethernet to a payload bay that can fit either a NUC or Jetson module (or other customer payload).
What exactly are we seeing in the video in terms of Digit’s autonomous capabilities?
At the moment this is a demonstration of shared autonomy. Picking and placing the box is fully autonomous. Balance and footstep placement are fully autonomous, but guidance and obstacle avoidance are under local teleop. It’s no longer a radio controller as in early videos; we’re not ready to reveal our current controller design but it’s a reasonably significant upgrade. This is v2 hardware, so there’s one more full version in development prior to the 2020 launch, which will expand the autonomy envelope significantly.
“This is a demonstration of shared autonomy. Picking and placing the box is fully autonomous. Balance and footstep placement are fully autonomous, but guidance and obstacle avoidance are under local teleop. It’s no longer a radio controller as in early videos; we’re not ready to reveal our current controller design but it’s a reasonably significant upgrade”
—Damion Shelton, Agility Robotics
What are some unique features or capabilities of Digit v2 that might not be obvious from the video?
For those who’ve used Cassie robots, the power-up and power-down ergonomics are a lot more user friendly. Digit can be disassembled into carry-on luggage sized pieces (give or take) in under 5 minutes for easy transport. The battery charges in-situ using a normal laptop-style charger.
I’m curious about this “stompy” sort of gait that we see in Digit and many other bipedal robots—are there significant challenges or drawbacks to implementing a more human-like (and presumably quieter) heel-toe gait?
There are no drawbacks other than increased complexity in controls and foot design. With Digit v2, the larger surface area helps with the noise, and v2 has similar or better passive-dynamic performance as compared to Cassie or Digit v1. The foot design is brand new, and new behaviors like heel-toe are an active area of development.
How close is Digit v2 to a system that you’d be comfortable operating commercially?
We’re on track for a 2020 launch for Digit v3. Changes from v2 to v3 are mostly bug-fix in nature, with a few regulatory upgrades like full battery certification. Safety is a major concern for us, and we have launch customers that will be operating Digit in a safe environment, with a phased approach to relaxing operational constraints. Digit operates almost exclusively under force control (as with cobots more generally), but at the moment we’ll err on the side of caution during operation until we have the stats to back up safety and reliability. The legged robot industry has too much potential for us to screw it up by behaving irresponsibly.
It will be a while before Digit (or any other humanoid robot) is operating fully autonomously in crowds of people, but there are so many large market opportunities (think indoor factory/warehouse environments) to address prior to that point that we expect to mature the operational safety side of things well in advance of having saturated the more robot-tolerant markets.
[ Agility Robotics ] Continue reading →
#436079 Video Friday: This Humanoid Robot Will ...
Video Friday is your weekly selection of awesome robotics videos, collected by your Automaton bloggers. We’ll also be posting a weekly calendar of upcoming robotics events for the next few months; here’s what we have so far (send us your events!):
Northeast Robotics Colloquium – October 12, 2019 – Philadelphia, Pa., USA
Ro-Man 2019 – October 14-18, 2019 – New Delhi, India
Humanoids 2019 – October 15-17, 2019 – Toronto, Canada
ARSO 2019 – October 31-1, 2019 – Beijing, China
ROSCon 2019 – October 31-1, 2019 – Macau
IROS 2019 – November 4-8, 2019 – Macau
Let us know if you have suggestions for next week, and enjoy today’s videos.
What’s better than a robotics paper with “dynamic” in the title? A robotics paper with “highly dynamic” in the title. From Sangbae Kim’s lab at MIT, the latest exploits of Mini Cheetah:
Yes I’d very much like one please. Full paper at the link below.
[ Paper ] via [ MIT ]
A humanoid robot serving you ice cream—on his own ice cream bike: What a delicious vision!
[ Roboy ]
The Roomba “i” series and “s” series vacuums have just gotten an update that lets you set “keep out” zones, which is super useful. Tell your robot where not to go!
I feel bad, that Roomba was probably just hungry 🙁
[ iRobot ]
We wrote about Voliro’s tilt-rotor hexcopter a couple years ago, and now it’s off doing practical things, like spray painting a building pretty much the same color that it was before.
[ Voliro ]
Thanks Mina!
Here’s a clever approach for bin-picking problematic objects, like shiny things: Just grab a whole bunch, and then sort out what you need on a nice robot-friendly table.
It might take a little bit longer, but what do you care, you’re probably off sipping a cocktail with a little umbrella in it on a beach somewhere.
[ Harada Lab ]
A unique combination of the IRB 1200 and YuMi industrial robots that use vision, AI and deep learning to recognize and categorize trash for recycling.
[ ABB ]
Measuring glacial movements in-situ is a challenging, but necessary task to model glaciers and predict their future evolution. However, installing GPS stations on ice can be dangerous and expensive when not impossible in the presence of large crevasses. In this project, the ASL develops UAVs for dropping and recovering lightweight GPS stations over inaccessible glaciers to record the ice flow motion. This video shows the results of first tests performed at Gorner glacier, Switzerland, in July 2019.
[ EPFL ]
Turns out Tertills actually do a pretty great job fighting weeds.
Plus, they leave all those cute lil’ Tertill tracks.
[ Franklin Robotics ]
The online autonomous navigation and semantic mapping experiment presented [below] is conducted with the Cassie Blue bipedal robot at the University of Michigan. The sensors attached to the robot include an IMU, a 32-beam LiDAR and an RGB-D camera. The whole online process runs in real-time on a Jetson Xavier and a laptop with an i7 processor.
The resulting map is so precise that it looks like we are doing real-time SLAM (simultaneous localization and mapping). In fact, the map is based on dead-reckoning via the InvEKF.
[ GTSAM ] via [ University of Michigan ]
UBTECH has announced an upgraded version of its Meebot, which is 30 percent bigger and comes with more sensors and programmable eyes.
[ UBTECH ]
ABB’s research team will be working with medical staff, scientist and engineers to develop non-surgical medical robotics systems, including logistics and next-generation automated laboratory technologies. The team will develop robotics solutions that will help eliminate bottlenecks in laboratory work and address the global shortage of skilled medical staff.
[ ABB ]
In this video, Ian and Chris go through Misty’s SDK, discussing the languages we’ve included, the tools that make it easy for you to get started quickly, a quick rundown of how to run the skills you build, plus what’s ahead on the Misty SDK roadmap.
[ Misty Robotics ]
My guess is that this was not one of iRobot’s testing environments for the Roomba.
You know, that’s actually super impressive. And maybe if they threw one of the self-emptying Roombas in there, it would be a viable solution to the entire problem.
[ How Farms Work ]
Part of WeRobotics’ Flying Labs network, Panama Flying Labs is a local knowledge hub catalyzing social good and empowering local experts. Through training and workshops, demonstrations and missions, the Panama Flying Labs team leverages the power of drones, data, and AI to promote entrepreneurship, build local capacity, and confront the pressing social challenges faced by communities in Panama and across Central America.
[ Panama Flying Labs ]
Go on a virtual flythrough of the NIOSH Experimental Mine, one of two courses used in the recent DARPA Subterranean Challenge Tunnel Circuit Event held 15-22 August, 2019. The data used for this partial flythrough tour were collected using 3D LIDAR sensors similar to the sensors commonly used on autonomous mobile robots.
[ SubT ]
Special thanks to PBS, Mark Knobil, Joe Seamans and Stan Brandorff and many others who produced this program in 1991.
It features Reid Simmons (and his 1 year old son), David Wettergreen, Red Whittaker, Mac Macdonald, Omead Amidi, and other Field Robotics Center alumni building the planetary walker prototype called Ambler. The team gets ready for an important demo for NASA.
[ CMU RI ]
As art and technology merge, roboticist Madeline Gannon explores the frontiers of human-robot interaction across the arts, sciences and society, and explores what this could mean for the future.
[ Sonar+D ] Continue reading →