Tag Archives: dodge

#437345 Moore’s Law Lives: Intel Says Chips ...

If you weren’t already convinced the digital world is taking over, you probably are now.

To keep the economy on life support as people stay home to stem the viral tide, we’ve been forced to digitize interactions at scale (for better and worse). Work, school, events, shopping, food, politics. The companies at the center of the digital universe are now powerhouses of the modern era—worth trillions and nearly impossible to avoid in daily life.

Six decades ago, this world didn’t exist.

A humble microchip in the early 1960s would have boasted a handful of transistors. Now, your laptop or smartphone runs on a chip with billions of transistors. As first described by Moore’s Law, this is possible because the number of transistors on a chip doubled with extreme predictability every two years for decades.

But now progress is faltering as the size of transistors approaches physical limits, and the money and time it takes to squeeze a few more onto a chip are growing. There’ve been many predictions that Moore’s Law is, finally, ending. But, perhaps also predictably, the company whose founder coined Moore’s Law begs to differ.

In a keynote presentation at this year’s Hot Chips conference, Intel’s chief architect, Raja Koduri, laid out a roadmap to increase transistor density—that is, the number of transistors you can fit on a chip—by a factor of 50.

“We firmly believe there is a lot more transistor density to come,” Koduri said. “The vision will play out over time—maybe a decade or more—but it will play out.”

Why the optimism?

Calling the end of Moore’s Law is a bit of a tradition. As Peter Lee, vice president at Microsoft Research, quipped to The Economist a few years ago, “The number of people predicting the death of Moore’s Law doubles every two years.” To date, prophets of doom have been premature, and though the pace is slowing, the industry continues to dodge death with creative engineering.

Koduri believes the trend will continue this decade and outlined the upcoming chip innovations Intel thinks can drive more gains in computing power.

Keeping It Traditional
First, engineers can further shrink today’s transistors. Fin field effect transistors (or FinFET) first hit the scene in the 2010s and have since pushed chip features past 14 and 10 nanometers (or nodes, as such size checkpoints are called). Korduri said FinFET will again triple chip density before it’s exhausted.

The Next Generation
FinFET will hand the torch off to nanowire transistors (also known as gate-all-around transistors).

Here’s how they’ll work. A transistor is made up of three basic components: the source, where current is introduced, the gate and channel, where current selectively flows, and the drain. The gate is like a light switch. It controls how much current flows through the channel. A transistor is “on” when the gate allows current to flow, and it’s off when no current flows. The smaller transistors get, the harder it is to control that current.

FinFET maintained fine control of current by surrounding the channel with a gate on three sides. Nanowire designs kick that up a notch by surrounding the channel with a gate on four sides (hence, gate-all-around). They’ve been in the works for years and are expected around 2025. Koduri said first-generation nanowire transistors will be followed by stacked nanowire transistors, and together, they’ll quadruple transistor density.

Building Up
Growing transistor density won’t only be about shrinking transistors, but also going 3D.

This is akin to how skyscrapers increase a city’s population density by adding more usable space on the same patch of land. Along those lines, Intel recently launched its Foveros chip design. Instead of laying a chip’s various “neighborhoods” next to each other in a 2D silicon sprawl, they’ve stacked them on top of each other like a layer cake. Chip stacking isn’t entirely new, but it’s advancing and being applied to general purpose CPUs, like the chips in your phone and laptop.

Koduri said 3D chip stacking will quadruple transistor density.

A Self-Fulfilling Prophecy
The technologies Koduri outlines are an evolution of the same general technology in use today. That is, we don’t need quantum computing or nanotube transistors to augment or replace silicon chips yet. Rather, as it’s done many times over the years, the chip industry will get creative with the design of its core product to realize gains for another decade.

Last year, veteran chip engineer Jim Keller, who at the time was Intel’s head of silicon engineering but has since left the company, told MIT Technology Review there are over a 100 variables driving Moore’s Law (including 3D architectures and new transistor designs). From the standpoint of pure performance, it’s also about how efficiently software uses all those transistors. Keller suggested that with some clever software tweaks “we could get chips that are a hundred times faster in 10 years.”

But whether Intel’s vision pans out as planned is far from certain.

Intel’s faced challenges recently, taking five years instead of two to move its chips from 14 nanometers to 10 nanometers. After a delay of six months for its 7-nanometer chips, it’s now a year behind schedule and lagging other makers who already offer 7-nanometer chips. This is a key point. Yes, chipmakers continue making progress, but it’s getting harder, more expensive, and timelines are stretching.

The question isn’t if Intel and competitors can cram more transistors onto a chip—which, Intel rival TSMC agrees is clearly possible—it’s how long will it take and at what cost?

That said, demand for more computing power isn’t going anywhere.

Amazon, Microsoft, Alphabet, Apple, and Facebook now make up a whopping 20 percent of the stock market’s total value. By that metric, tech is the most dominant industry in at least 70 years. And new technologies—from artificial intelligence and virtual reality to a proliferation of Internet of Things devices and self-driving cars—will demand better chips.

There’s ample motivation to push computing to its bitter limits and beyond. As is often said, Moore’s Law is a self-fulfilling prophecy, and likely whatever comes after it will be too.

Image credit: Laura Ockel / Unsplash Continue reading

Posted in Human Robots

#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.

[ Skydio ] Continue reading

Posted in Human Robots

#435791 To Fly Solo, Racing Drones Have a Need ...

Drone racing’s ultimate vision of quadcopters weaving nimbly through obstacle courses has attracted far less excitement and investment than self-driving cars aimed at reshaping ground transportation. But the U.S. military and defense industry are betting on autonomous drone racing as the next frontier for developing AI so that it can handle high-speed navigation within tight spaces without human intervention.

The autonomous drone challenge requires split-second decision-making with six degrees of freedom instead of a car’s mere two degrees of road freedom. One research team developing the AI necessary for controlling autonomous racing drones is the Robotics and Perception Group at the University of Zurich in Switzerland. In late May, the Swiss researchers were among nine teams revealed to be competing in the two-year AlphaPilot open innovation challenge sponsored by U.S. aerospace company Lockheed Martin. The winning team will walk away with up to $2.25 million for beating other autonomous racing drones and a professional human drone pilot in head-to-head competitions.

“I think it is important to first point out that having an autonomous drone to finish a racing track at high speeds or even beating a human pilot does not imply that we can have autonomous drones [capable of] navigating in real-world, complex, unstructured, unknown environments such as disaster zones, collapsed buildings, caves, tunnels or narrow pipes, forests, military scenarios, and so on,” says Davide Scaramuzza, a professor of robotics and perception at the University of Zurich and ETH Zurich. “However, the robust and computationally efficient state estimation algorithms, control, and planning algorithms developed for autonomous drone racing would represent a starting point.”

The nine teams that made the cut—from a pool of 424 AlphaPilot applicants—will compete in four 2019 racing events organized under the Drone Racing League’s Artificial Intelligence Robotic Racing Circuit, says Keith Lynn, program manager for AlphaPilot at Lockheed Martin. To ensure an apples-to-apples comparison of each team’s AI secret sauce, each AlphaPilot team will upload its AI code into identical, specially-built drones that have the NVIDIA Xavier GPU at the core of the onboard computing hardware.

“Lockheed Martin is offering mentorship to the nine AlphaPilot teams to support their AI tech development and innovations,” says Lynn. The company “will be hosting a week-long Developers Summit at MIT in July, dedicated to workshopping and improving AlphaPilot teams’ code,” he added. He notes that each team will retain the intellectual property rights to its AI code.

The AlphaPilot challenge takes inspiration from older autonomous drone racing events hosted by academic researchers, Scaramuzza says. He credits Hyungpil Moon, a professor of robotics and mechanical engineering at Sungkyunkwan University in South Korea, for having organized the annual autonomous drone racing competition at the International Conference on Intelligent Robots and Systems since 2016.

It’s no easy task to create and train AI that can perform high-speed flight through complex environments by relying on visual navigation. One big challenge comes from how drones can accelerate sharply, take sharp turns, fly sideways, do zig-zag patterns and even perform back flips. That means camera images can suddenly appear tilted or even upside down during drone flight. Motion blur may occur when a drone flies very close to structures at high speeds and camera pixels collect light from multiple directions. Both cameras and visual software can also struggle to compensate for sudden changes between light and dark parts of an environment.

To lend AI a helping hand, Scaramuzza’s group recently published a drone racing dataset that includes realistic training data taken from a drone flown by a professional pilot in both indoor and outdoor spaces. The data, which includes complicated aerial maneuvers such as back flips, flight sequences that cover hundreds of meters, and flight speeds of up to 83 kilometers per hour, was presented at the 2019 IEEE International Conference on Robotics and Automation.

The drone racing dataset also includes data captured by the group’s special bioinspired event cameras that can detect changes in motion on a per-pixel basis within microseconds. By comparison, ordinary cameras need milliseconds (each millisecond being 1,000 microseconds) to compare motion changes in each image frame. The event cameras have already proven capable of helping drones nimbly dodge soccer balls thrown at them by the Swiss lab’s researchers.

The Swiss group’s work on the racing drone dataset received funding in part from the U.S. Defense Advanced Research Projects Agency (DARPA), which acts as the U.S. military’s special R&D arm for more futuristic projects. Specifically, the funding came from DARPA’s Fast Lightweight Autonomy program that envisions small autonomous drones capable of flying at high speeds through cluttered environments without GPS guidance or communication with human pilots.

Such speedy drones could serve as military scouts checking out dangerous buildings or alleys. They could also someday help search-and-rescue teams find people trapped in semi-collapsed buildings or lost in the woods. Being able to fly at high speed without crashing into things also makes a drone more efficient at all sorts of tasks by making the most of limited battery life, Scaramuzza says. After all, most drone battery life gets used up by the need to hover in flight and doesn’t get drained much by flying faster.

Even if AI manages to conquer the drone racing obstacle courses, that would be the end of the beginning of the technology’s development. What would still be required? Scaramuzza specifically singled out the need to handle low-visibility conditions involving smoke, dust, fog, rain, snow, fire, hail, as some of the biggest challenges for vision-based algorithms and AI in complex real-life environments.

“I think we should develop and release datasets containing smoke, dust, fog, rain, fire, etc. if we want to allow using autonomous robots to complement human rescuers in saving people lives after an earthquake or natural disaster in the future,” Scaramuzza says. Continue reading

Posted in Human Robots