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#437924 How a Software Map of the Entire Planet ...

“3D map data is the scaffolding of the 21st century.”

–Edward Miller, Founder, Scape Technologies, UK

Covered in cameras, sensors, and a distinctly spaceship looking laser system, Google’s autonomous vehicles were easy to spot when they first hit public roads in 2015. The key hardware ingredient is a spinning laser fixed to the roof, called lidar, which provides the car with a pair of eyes to see the world. Lidar works by sending out beams of light and measuring the time it takes to bounce off objects back to the source. By timing the light’s journey, these depth-sensing systems construct fully 3D maps of their surroundings.

3D maps like these are essentially software copies of the real world. They will be crucial to the development of a wide range of emerging technologies including autonomous driving, drone delivery, robotics, and a fast-approaching future filled with augmented reality.

Like other rapidly improving technologies, lidar is moving quickly through its development cycle. What was an expensive technology on the roof of a well-funded research project is now becoming cheaper, more capable, and readily available to consumers. At some point, lidar will come standard on most mobile devices and is now available to early-adopting owners of the iPhone 12 Pro.

Consumer lidar represents the inevitable shift from wealthy tech companies generating our world’s map data, to a more scalable crowd-sourced approach. To develop the repository for their Street View Maps product, Google reportedly spent $1-2 billion sending cars across continents photographing every street. Compare that to a live-mapping service like Waze, which uses crowd-sourced user data from its millions of users to generate accurate and real-time traffic conditions. Though these maps serve different functions, one is a static, expensive, unchanging map of the world while the other is dynamic, real-time, and constructed by users themselves.

Soon millions of people may be scanning everything from bedrooms to neighborhoods, resulting in 3D maps of significant quality. An online search for lidar room scans demonstrates just how richly textured these three-dimensional maps are compared to anything we’ve had before. With lidar and other depth-sensing systems, we now have the tools to create exact software copies of everywhere and everything on earth.

At some point, likely aided by crowdsourcing initiatives, these maps will become living breathing, real-time representations of the world. Some refer to this idea as a “digital twin” of the planet. In a feature cover story, Kevin Kelly, the cofounder of Wired magazine, calls this concept the “mirrorworld,” a one-to-one software map of everything.

So why is that such a big deal? Take augmented reality as an example.

Of all the emerging industries dependent on such a map, none are more invested in seeing this concept emerge than those within the AR landscape. Apple, for example, is not-so-secretly developing a pair of AR glasses, which they hope will deliver a mainstream turning point for the technology.

For Apple’s AR devices to work as anticipated, they will require virtual maps of the world, a concept AR insiders call the “AR cloud,” which is synonymous with the “mirrorworld” concept. These maps will be two things. First, they will be a tool that creators use to place AR content in very specific locations; like a world canvas to paint on. Second, they will help AR devices both locate and understand the world around them so they can render content in a believable way.

Imagine walking down a street wanting to check the trading hours of a local business. Instead of pulling out your phone to do a tedious search online, you conduct the equivalent of a visual google search simply by gazing at the store. Albeit a trivial example, the AR cloud represents an entirely non-trivial new way of managing how we organize the world’s information. Access to knowledge can be shifted away from the faraway monitors in our pocket, to its relevant real-world location.

Ultimately this describes a blurring of physical and digital infrastructure. Our public and private spaces will thus be comprised equally of both.

No example demonstrates this idea better than Pokémon Go. The game is straightforward enough; users capture virtual characters scattered around the real world. Today, the game relies on traditional GPS technology to place its characters, but GPS is accurate only to within a few meters of a location. For a car navigating on a highway or locating Pikachus in the world, that level of precision is sufficient. For drone deliveries, driverless cars, or placing a Pikachu in a specific location, say on a tree branch in a park, GPS isn’t accurate enough. As astonishing as it may seem, many experimental AR cloud concepts, even entirely mapped cities, are location specific down to the centimeter.

Niantic, the $4 billion publisher behind Pokémon Go, is aggressively working on developing a crowd-sourced approach to building better AR Cloud maps by encouraging their users to scan the world for them. Their recent acquisition of 6D.ai, a mapping software company developed by the University of Oxford’s Victor Prisacariu through his work at Oxford’s Active Vision Lab, indicates Niantic’s ambition to compete with the tech giants in this space.

With 6D.ai’s technology, Niantic is developing the in-house ability to generate their own 3D maps while gaining better semantic understanding of the world. By going beyond just knowing there’s a temporary collection of orange cones in a certain location, for example, the game may one day understand the meaning behind this; that a temporary construction zone means no Pokémon should spawn here to avoid drawing players to this location.

Niantic is not the only company working on this. Many of the big tech firms you would expect have entire teams focused on map data. Facebook, for example, recently acquired the UK-based Scape technologies, a computer vision startup mapping entire cities with centimeter precision.

As our digital maps of the world improve, expect a relentless and justified discussion of privacy concerns as well. How will society react to the idea of a real-time 3D map of their bedroom living on a Facebook or Amazon server? Those horrified by the use of facial recognition AI being used in public spaces are unlikely to find comfort in the idea of a machine-readable world subject to infinite monitoring.

The ability to build high-precision maps of the world could reshape the way we engage with our planet and promises to be one of the biggest technology developments of the next decade. While these maps may stay hidden as behind-the-scenes infrastructure powering much flashier technologies that capture the world’s attention, they will soon prop up large portions of our technological future.

Keep that in mind when a car with no driver is sharing your road.

Image credit: sergio souza / Pexels Continue reading

Posted in Human Robots

#437851 Boston Dynamics’ Spot Robot Dog ...

Boston Dynamics has been fielding questions about when its robots are going to go on sale and how much they’ll cost for at least a dozen years now. I can say this with confidence, because that’s how long I’ve been a robotics journalist, and I’ve been pestering them about it the entire time. But it’s only relatively recently that the company started to make a concerted push away from developing robots exclusively for the likes of DARPA into platforms with more commercial potential, starting with a compact legged robot called Spot, first introduced in 2016.

Since then, we’ve been following closely as Spot has gone from a research platform to a product, and today, Boston Dynamics is announcing the final step in that process: commercial availability. You can now order a Spot Explorer Kit from the Boston Dynamics online store for US $74,500 (plus tax), shipping included, with delivery in 6 to 8 weeks. FINALLY!

Over the past 10 months or so, Boston Dynamics has leased Spot robots to carefully selected companies, research groups, and even a few individuals as part of their early adopter program—that’s where all of the clips in the video below came from. While there are over 100 Spots out in the world right now, getting one of them has required convincing Boston Dynamics up front that you knew more or less exactly what you wanted to do and how you wanted to do it. If you’re a big construction company or the Jet Propulsion Laboratory or Adam Savage, that’s all well and good, but for other folks who think that a Spot could be useful for them somehow and want to give it a shot, this new availability provides a fewer-strings attached opportunity to do some experimentation with the robot.

There’s a lot of cool stuff going on in that video, but we were told that the one thing that really stood out to the folks at Boston Dynamics was a 2-second clip that you can see on the left-hand side of the screen from 0:19 to 0:21. In it, Spot is somehow managing to walk across a spider web of rebar without getting tripped up, at faster than human speed. This isn’t something that Spot was specifically programmed to do, and in fact the Spot User Guide specifically identifies “rebar mesh” as an unsafe operating environment. But the robot just handles it, and that’s a big part of what makes Spot so useful—its ability to deal with (almost) whatever you can throw at it.

Before you get too excited, Boston Dynamics is fairly explicit that the current license for the robot is intended for commercial use, and the company specifically doesn’t want people to be just using it at home for fun. We know this because we asked (of course we asked), and they told us “we specifically don’t want people to just be using it at home for fun.” Drat. You can still buy one as an individual, but you have to promise that you’ll follow the terms of use and user guidelines, and it sounds like using a robot in your house might be the second-fastest way to invalidate your warranty:


Not being able to get Spot to play with your kids may be disappointing, but for those of you with the sort of kids who are also students, the good news is that Boston Dynamics has carved out a niche for academic institutions, which can buy Spot at a discounted price. And if you want to buy a whole pack of Spots, there’s a bulk discount for Enterprise users as well.

What do you get for $74,500? All this!

Spot robot
Spot battery (2x)
Spot charger
Tablet controller and charger
Robot case for storage and transportation

Photo: Boston Dynamics

The basic package includes the robot, two batteries, charger, a tablet controller, and a storage case.

You can view detailed specs here.

So is $75k a lot of money for a robot like Spot, or not all that much? We don’t have many useful points of comparison, partially because it’s not clear to what extent other pre-commercial quadrupedal robots (like ANYmal or Aliengo) share capabilities and features with Spot. For more perspective on Spot’s price tag, we spoke to Michael Perry, vice president of business development at Boston Dynamics.

IEEE Spectrum: Why is Spot so affordable?

Michael Perry: The main goal of selling the robot at this stage is to try to get it into the hands of as many application developers as possible, so that we can learn from the community what the biggest driver of value is for Spot. As a platform, unlocking the value of an ecosystem is our core focus right now.

Spectrum: Why is Spot so expensive?

Perry: Expensive is relative, but compared to the initial prototypes of Spot, we’ve been able to drop down the cost pretty significantly. One key thing has been designing it for robustness—we’ve put hundreds and hundreds of hours on the robot to make sure that it’s able to be successful when it falls, or when it has an electrostatic discharge. We’ve made sure that it’s able to perceive a wide variety of environments that are difficult for traditional vision-based sensors to handle. A lot of that engineering is baked into the core product so that you don’t have to worry about the mobility or robotic side of the equation, you can just focus on application development.

Photos: Boston Dynamics

Accessories for Spot include [clockwise from top left]: Spot GXP with additional ports for payload integration; Spot CAM with panorama camera and advanced comms; Spot CAM+ with pan-tilt-zoom camera for inspections; Spot EAP with lidar to enhance autonomy on large sites; Spot EAP+ with Spot CAM camera plus lidar; and Spot CORE for additional processing power.

The $75k that you’ll pay for the Spot Explorer Kit, it’s important to note, is just the base price for the robot. As with other things that fall into this price range (like a luxury car), there are all kinds of fun ways to drive that cost up with accessories, although for Spot, some of those accessories will be necessary for many (if not most) applications. For example, a couple of expansion ports to make it easier to install your own payloads on Spot will run you $1,275. An additional battery is $4,620. And if you want to really get some work done, the Enhanced Autonomy Package (with 360 cameras, lights, better comms, and a Velodyne VLP-16) will set you back an additional $34,570. If you were hoping for an arm, you’ll have to wait until the end of the year.

Each Spot also includes a year’s worth of software updates and a warranty, although the standard warranty just covers “defects related to materials and workmanship” not “I drove my robot off a cliff” or “I tried to take my robot swimming.” For that sort of thing (user error) to be covered, you’ll need to upgrade to the $12,000 Spot CARE premium service plan to cover your robot for a year as long as you don’t subject it to willful abuse, which both of those examples I just gave probably qualify as.

While we’re on the subject of robot abuse, Boston Dynamics has very sensibly devoted a substantial amount of the Spot User Guide to help new users understand how they should not be using their robot, in order to “lessen the risk of serious injury, death, or robot and other property damage.” According to the guide, some things that could cause Spot to fall include holes, cliffs, slippery surfaces (like ice and wet grass), and cords. Spot’s sensors also get confused by “transparent, mirrored, or very bright obstacles,” and the guide specifically says Spot “may crash into glass doors and windows.” Also this: “Spot cannot predict trajectories of moving objects. Do not operate Spot around moving objects such as vehicles, children, or pets.”

We should emphasize that this is all totally reasonable, and while there are certainly a lot of things to be aware of, it’s frankly astonishing that these are the only things that Boston Dynamics explicitly warns users against. Obviously, not every potentially unsafe situation or thing is described above, but the point is that Boston Dynamics is willing to say to new users, “here’s your robot, go do stuff with it” without feeling the need to hold their hand the entire time.

There’s one more thing to be aware of before you decide to buy a Spot, which is the following:

“All orders will be subject to Boston Dynamics’ Terms and Conditions of Sale which require the beneficial use of its robots.”

Specifically, this appears to mean that you aren’t allowed to (or supposed to) use the robot in a way that could hurt living things, or “as a weapon, or to enable any weapon.” The conditions of sale also prohibit using the robot for “any illegal or ultra-hazardous purpose,” and there’s some stuff in there about it not being cool to use Spot for “nuclear, chemical, or biological weapons proliferation, or development of missile technology,” which seems weirdly specific.

“Once you make a technology more broadly available, the story of it starts slipping out of your hands. Our hope is that ahead of time we’re able to clearly articulate the beneficial uses of the robot in environments where we think the robot has a high potential to reduce the risk to people, rather than potentially causing harm.”
—Michael Perry, Boston Dynamics

I’m very glad that Boston Dynamics is being so upfront about requiring that Spot is used beneficially. However, it does put the company in a somewhat challenging position now that these robots are being sold. Boston Dynamics can (and will) perform some amount of due-diligence before shipping a Spot, but ultimately, once the robots are in someone else’s hands, there’s only so much that BD can do.

Spectrum: Why is beneficial use important to Boston Dynamics?

Perry: One of the key things that we’ve highlighted many times in our license and terms of use is that we don’t want to see the robot being used in any way that inflicts physical harm on people or animals. There are philosophical reasons for that—I think all of us don’t want to see our technology used in a way that would hurt people. But also from a business perspective, robots are really terrible at conveying intention. In order for the robot to be helpful long-term, it has to be trusted as a piece of technology. So rather than looking at a robot and wondering, “is this something that could potentially hurt me,” we want people to think “this is a robot that’s here to help me.” To the extent that people associate Boston Dynamics with cutting edge robots, we think that this is an important stance for the rollout of our first commercial product. If we find out that somebody’s violated our terms of use, their warranty is invalidated, we won’t repair their product, and we have a licensing timeout that would prevent them from accessing their robot after that timeout has expired. It’s a remediation path, but we do think that it’s important to at least provide that as something that helps enforce our position on use of our technology.

It’s very important to keep all of this in context: Spot is a tool. It’s got some autonomy and the appearance of agency, but it’s still just doing what people tell it to do, even if those things might be unsafe. If you read through the user guide, it’s clear how much of an effort Boston Dynamics is making to try to convey the importance of safety to Spot users—and ultimately, barring some unforeseen and catastrophic software or hardware issues, safety is about the users, rather than Boston Dynamics or Spot itself. I bring this up because as we start seeing more and more Spots doing things without Boston Dynamics watching over them quite so closely, accidents are likely inevitable. Spot might step on someone’s foot. It might knock someone over. If Spot was perfectly safe, it wouldn’t be useful, and we have to acknowledge that its impressive capabilities come with some risks, too.

Photo: Boston Dynamics

Each Spot includes a year’s worth of software updates and a warranty, although the standard warranty just covers “defects related to materials and workmanship” not “I drove my robot off a cliff.”

Now that Spot is on the market for real, we’re excited to see who steps up and orders one. Depending on who the potential customer is, Spot could either seem like an impossibly sophisticated piece of technology that they’d never be able to use, or a magical way of solving all of their problems overnight. In reality, it’s of course neither of those things. For the former (folks with an idea but without a lot of robotics knowledge or experience), Spot does a lot out of the box, but BD is happy to talk with people and facilitate connections with partners who might be able to integrate specific software and hardware to get Spot to do a unique task. And for the latter (who may also be folks with an idea but without a lot of robotics knowledge or experience), BD’s Perry offers a reminder Spot is not Rosie the Robot, and would be equally happy to talk about what the technology is actually capable of doing.

Looking forward a bit, we asked Perry whether Spot’s capabilities mean that customers are starting to think beyond using robots to simply replace humans, and are instead looking at them as a way of enabling a completely different way of getting things done.

Spectrum: Do customers interested in Spot tend to think of it as a way of replacing humans at a specific task, or as a system that can do things that humans aren’t able to do?

Perry: There are what I imagine as three levels of people understanding the robot applications. Right now, we’re at level one, where you take a person out of this dangerous, dull job, and put a robot in. That’s the entry point. The second level is, using the robot, can we increase the production of that task? For example, take site documentation on a construction site—right now, people do 360 image capture of a site maybe once a week, and they might do a laser scan of the site once per project. At the second level, the question is, what if you were able to get that data collection every day, or multiple times a day? What kinds of benefits would that add to your process? To continue the construction example, the third level would be, how could we completely redesign this space now that we know that this type of automation is available? To take one example, there are some things that we cannot physically build because it’s too unsafe for people to be a part of that process, but if you were to apply robotics to that process, then you could potentially open up a huge envelope of design that has been inaccessible to people.

To order a Spot of your very own, visit shop.bostondynamics.com.

A version of this post appears in the August 2020 print issue as “$74,500 Will Fetch You a Spot.” Continue reading

Posted in Human Robots

#437765 Video Friday: Massive Robot Joins ...

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!):

AWS Cloud Robotics Summit – August 18-19, 2020 – [Online Conference]
CLAWAR 2020 – August 24-26, 2020 – [Virtual Conference]
ICUAS 2020 – September 1-4, 2020 – Athens, Greece
ICRES 2020 – September 28-29, 2020 – Taipei, Taiwan
IROS 2020 – October 25-29, 2020 – Las Vegas, Nevada
ICSR 2020 – November 14-16, 2020 – Golden, Colorado
Let us know if you have suggestions for next week, and enjoy today’s videos.

Here are some professional circus artists messing around with an industrial robot for fun, like you do.

The acrobats are part of Östgötateatern, a Swedish theatre group, and the chair bit got turned into its own act, called “The Last Fish.” But apparently the Swedish Work Environment Authority didn’t like that an industrial robot—a large ABB robotic arm—was being used in an artistic performance, arguing that the same safety measures that apply in a factory setting would apply on stage. In other words, the robot had to operate inside a protective cage and humans could not physically interact with it.

When told that their robot had to be removed, the acrobats went to court. And won! At least that’s what we understand from this Swedish press release. The court in Linköping, in southern Sweden, ruled that the safety measures taken by the theater had been sufficient. The group had worked with a local robotics firm, Dyno Robotics, to program the manipulator and learn how to interact with it as safely as possible. The robot—which the acrobats say is the eighth member of their troupe—will now be allowed to return.

[ Östgötateatern ]

Houston Mechathronics’ Aquanaut continues to be awesome, even in the middle of a pandemic. It’s taken the big step (big swim?) out of NASA’s swimming pool and into open water.

[ HMI ]

Researchers from Carnegie Mellon University and Facebook AI Research have created a navigation system for robots powered by common sense. The technique uses machine learning to teach robots how to recognize objects and understand where they’re likely to be found in house. The result allows the machines to search more strategically.

[ CMU ]

Cassie manages 2.1 m/s, which is uncomfortably fast in a couple of different ways.

Next, untethered. After that, running!

[ Michigan Robotics ]

Engineers at Caltech have designed a new data-driven method to control the movement of multiple robots through cluttered, unmapped spaces, so they do not run into one another.

Multi-robot motion coordination is a fundamental robotics problem with wide-ranging applications that range from urban search and rescue to the control of fleets of self-driving cars to formation-flying in cluttered environments. Two key challenges make multi-robot coordination difficult: first, robots moving in new environments must make split-second decisions about their trajectories despite having incomplete data about their future path; second, the presence of larger numbers of robots in an environment makes their interactions increasingly complex (and more prone to collisions).

To overcome these challenges, Soon-Jo Chung, Bren Professor of Aerospace, and Yisong Yue, professor of computing and mathematical sciences, along with Caltech graduate student Benjamin Rivière (MS ’18), postdoctoral scholar Wolfgang Hönig, and graduate student Guanya Shi, developed a multi-robot motion-planning algorithm called “Global-to-Local Safe Autonomy Synthesis,” or GLAS, which imitates a complete-information planner with only local information, and “Neural-Swarm,” a swarm-tracking controller augmented to learn complex aerodynamic interactions in close-proximity flight.

[ Caltech ]

Fetch Robotics’ Freight robot is now hauling around pulsed xenon UV lamps to autonomously disinfect spaces with UV-A, UV-B, and UV-C, all at the same time.

[ SmartGuard UV ]

When you’re a vertically symmetrical quadruped robot, there is no upside-down.

[ Ghost Robotics ]

In the virtual world, the objects you pick up do not exist: you can see that cup or pen, but it does not feel like you’re touching them. That presented a challenge to EPFL professor Herbert Shea. Drawing on his extensive experience with silicone-based muscles and motors, Shea wanted to find a way to make virtual objects feel real. “With my team, we’ve created very small, thin and fast actuators,” explains Shea. “They are millimeter-sized capsules that use electrostatic energy to inflate and deflate.” The capsules have an outer insulating membrane made of silicone enclosing an inner pocket filled with oil. Each bubble is surrounded by four electrodes, that can close like a zipper. When a voltage is applied, the electrodes are pulled together, causing the center of the capsule to swell like a blister. It is an ingenious system because the capsules, known as HAXELs, can move not only up and down, but also side to side and around in a circle. “When they are placed under your fingers, it feels as though you are touching a range of different objects,” says Shea.

[ EPFL ]

Through the simple trick of reversing motors on impact, a quadrotor can land much more reliably on slopes.

[ Sherbrooke ]

Turtlebot delivers candy at Harvard.

I <3 Turtlebot SO MUCH

[ Harvard ]

Traditional drone controllers are a little bit counterintuitive, because there’s one stick that’s forwards and backwards and another stick that’s up and down but they’re both moving on the same axis. How does that make sense?! Here’s a remote that gives you actual z-axis control instead.

[ Fenics ]

Thanks Ashley!

Lio is a mobile robot platform with a multifunctional arm explicitly designed for human-robot interaction and personal care assistant tasks. The robot has already been deployed in several health care facilities, where it is functioning autonomously, assisting staff and patients on an everyday basis.

[ F&P Robotics ]

Video shows a ground vehicle autonomously exploring and mapping a multi-storage garage building and a connected patio on Carnegie Mellon University campus. The vehicle runs onboard state estimation and mapping leveraging range, vision, and inertial sensing, local planning for collision avoidance, and terrain analysis. All processing is real-time and no post-processing involved. The vehicle drives at 2m/s through the exploration run. This work is dedicated to DARPA Subterranean Challange.

[ CMU ]

Raytheon UK’s flagship STEM programme, the Quadcopter Challenge, gives 14-15 year olds the chance to participate in a hands-on, STEM-based engineering challenge to build a fully operational quadcopter. Each team is provided with an identical kit of parts, tools and instructions to build and customise their quadcopter, whilst Raytheon UK STEM Ambassadors provide mentoring, technical support and deliver bite-size learning modules to support the build.

[ Raytheon ]

A video on some of the research work that is being carried out at The Australian Centre for Field Robotics, University of Sydney.

[ University of Sydney ]

Jeannette Bohg, assistant professor of computer science at Stanford University, gave one of the Early Career Award Keynotes at RSS 2020.

[ RSS 2020 ]

Adam Savage remembers Grant Imahara.

[ Tested ] Continue reading

Posted in Human Robots

#437709 iRobot Announces Major Software Update, ...

Since the release of the very first Roomba in 2002, iRobot’s long-term goal has been to deliver cleaner floors in a way that’s effortless and invisible. Which sounds pretty great, right? And arguably, iRobot has managed to do exactly this, with its most recent generation of robot vacuums that make their own maps and empty their own dustbins. For those of us who trust our robots, this is awesome, but iRobot has gradually been realizing that many Roomba users either don’t want this level of autonomy, or aren’t ready for it.

Today, iRobot is announcing a major new update to its app that represents a significant shift of its overall approach to home robot autonomy. Humans are being brought back into the loop through software that tries to learn when, where, and how you clean so that your Roomba can adapt itself to your life rather than the other way around.

To understand why this is such a shift for iRobot, let’s take a very brief look back at how the Roomba interface has evolved over the last couple of decades. The first generation of Roomba had three buttons on it that allowed (or required) the user to select whether the room being vacuumed was small or medium or large in size. iRobot ditched that system one generation later, replacing the room size buttons with one single “clean” button. Programmable scheduling meant that users no longer needed to push any buttons at all, and with Roombas able to find their way back to their docking stations, all you needed to do was empty the dustbin. And with the most recent few generations (the S and i series), the dustbin emptying is also done for you, reducing direct interaction with the robot to once a month or less.

Image: iRobot

iRobot CEO Colin Angle believes that working toward more intelligent human-robot collaboration is “the brave new frontier” of AI. “This whole journey has been earning the right to take this next step, because a robot can’t be responsive if it’s incompetent,” he says. “But thinking that autonomy was the destination was where I was just completely wrong.”

The point that the top-end Roombas are at now reflects a goal that iRobot has been working toward since 2002: With autonomy, scheduling, and the clean base to empty the bin, you can set up your Roomba to vacuum when you’re not home, giving you cleaner floors every single day without you even being aware that the Roomba is hard at work while you’re out. It’s not just hands-off, it’s brain-off. No noise, no fuss, just things being cleaner thanks to the efforts of a robot that does its best to be invisible to you. Personally, I’ve been completely sold on this idea for home robots, and iRobot CEO Colin Angle was as well.

“I probably told you that the perfect Roomba is the Roomba that you never see, you never touch, you just come home everyday and it’s done the right thing,” Angle told us. “But customers don’t want that—they want to be able to control what the robot does. We started to hear this a couple years ago, and it took a while before it sunk in, but it made sense.”

How? Angle compares it to having a human come into your house to clean, but you weren’t allowed to tell them where or when to do their job. Maybe after a while, you’ll build up the amount of trust necessary for that to work, but in the short term, it would likely be frustrating. And people get frustrated with their Roombas for this reason. “The desire to have more control over what the robot does kept coming up, and for me, it required a pretty big shift in my view of what intelligence we were trying to build. Autonomy is not intelligence. We need to do something more.”

That something more, Angle says, is a partnership as opposed to autonomy. It’s an acknowledgement that not everyone has the same level of trust in robots as the people who build them. It’s an understanding that people want to have a feeling of control over their homes, that they have set up the way that they want, and that they’ve been cleaning the way that they want, and a robot shouldn’t just come in and do its own thing.

This change in direction also represents a substantial shift in resources for iRobot, and the company has pivoted two-thirds of its engineering organization to focus on software-based collaborative intelligence rather than hardware.

“Until the robot proves that it knows enough about your home and about the way that you want your home cleaned,” Angle says, “you can’t move forward.” He adds that this is one of those things that seem obvious in retrospect, but even if they’d wanted to address the issue before, they didn’t have the technology to solve the problem. Now they do. “This whole journey has been earning the right to take this next step, because a robot can’t be responsive if it’s incompetent,” Angle says. “But thinking that autonomy was the destination was where I was just completely wrong.”

The previous iteration of the iRobot app (and Roombas themselves) are built around one big fat CLEAN button. The new approach instead tries to figure out in much more detail where the robot should clean, and when, using a mixture of autonomous technology and interaction with the user.

Where to Clean
Knowing where to clean depends on your Roomba having a detailed and accurate map of its environment. For several generations now, Roombas have been using visual mapping and localization (VSLAM) to build persistent maps of your home. These maps have been used to tell the Roomba to clean in specific rooms, but that’s about it. With the new update, Roombas with cameras will be able to recognize some objects and features in your home, including chairs, tables, couches, and even countertops. The robots will use these features to identify where messes tend to happen so that they can focus on those areas—like around the dining room table or along the front of the couch.

We should take a minute here to clarify how the Roomba is using its camera. The original (primary?) purpose of the camera was for VSLAM, where the robot would take photos of your home, downsample them into QR-code-like patterns of light and dark, and then use those (with the assistance of other sensors) to navigate. Now the camera is also being used to take pictures of other stuff around your house to make that map more useful.

Photo: iRobot

The robots will now try to fit into the kinds of cleaning routines that many people already have established. For example, the app may suggest an “after dinner” routine that cleans just around the kitchen and dining room table.

This is done through machine learning using a library of images of common household objects from a floor perspective that iRobot had to develop from scratch. Angle clarified for us that this is all done via a neural net that runs on the robot, and that “no recognizable images are ever stored on the robot or kept, and no images ever leave the robot.” Worst case, if all the data iRobot has about your home gets somehow stolen, the hacker would only know that (for example) your dining room has a table in it and the approximate size and location of that table, because the map iRobot has of your place only stores symbolic representations rather than images.

Another useful new feature is intended to help manage the “evil Roomba places” (as Angle puts it) that every home has that cause Roombas to get stuck. If the place is evil enough that Roomba has to call you for help because it gave up completely, Roomba will now remember, and suggest that either you make some changes or that it stops cleaning there, which seems reasonable.

When to Clean
It turns out that the primary cause of mission failure for Roombas is not that they get stuck or that they run out of battery—it’s user cancellation, usually because the robot is getting in the way or being noisy when you don’t want it to be. “If you kill a Roomba’s job because it annoys you,” points out Angle, “how is that robot being a good partner? I think it’s an epic fail.” Of course, it’s not the robot’s fault, because Roombas only clean when we tell them to, which Angle says is part of the problem. “People actually aren’t very good at making their own schedules—they tend to oversimplify, and not think through what their schedules are actually about, which leads to lots of [figurative] Roomba death.”

To help you figure out when the robot should actually be cleaning, the new app will look for patterns in when you ask the robot to clean, and then recommend a schedule based on those patterns. That might mean the robot cleans different areas at different times every day of the week. The app will also make scheduling recommendations that are event-based as well, integrated with other smart home devices. Would you prefer the Roomba to clean every time you leave the house? The app can integrate with your security system (or garage door, or any number of other things) and take care of that for you.

More generally, Roomba will now try to fit into the kinds of cleaning routines that many people already have established. For example, the app may suggest an “after dinner” routine that cleans just around the kitchen and dining room table. The app will also, to some extent, pay attention to the environment and season. It might suggest increasing your vacuuming frequency if pollen counts are especially high, or if it’s pet shedding season and you have a dog. Unfortunately, Roomba isn’t (yet?) capable of recognizing dogs on its own, so the app has to cheat a little bit by asking you some basic questions.

A Smarter App

Image: iRobot

The previous iteration of the iRobot app (and Roombas themselves) are built around one big fat CLEAN button. The new approach instead tries to figure out in much more detail where the robot should clean, and when, using a mixture of autonomous technology and interaction with the user.

The app update, which should be available starting today, is free. The scheduling and recommendations will work on every Roomba model, although for object recognition and anything related to mapping, you’ll need one of the more recent and fancier models with a camera. Future app updates will happen on a more aggressive schedule. Major app releases should happen every six months, with incremental updates happening even more frequently than that.

Angle also told us that overall, this change in direction also represents a substantial shift in resources for iRobot, and the company has pivoted two-thirds of its engineering organization to focus on software-based collaborative intelligence rather than hardware. “It’s not like we’re done doing hardware,” Angle assured us. “But we do think about hardware differently. We view our robots as platforms that have longer life cycles, and each platform will be able to support multiple generations of software. We’ve kind of decoupled robot intelligence from hardware, and that’s a change.”

Angle believes that working toward more intelligent collaboration between humans and robots is “the brave new frontier of artificial intelligence. I expect it to be the frontier for a reasonable amount of time to come,” he adds. “We have a lot of work to do to create the type of easy-to-use experience that consumer robots need.” Continue reading

Posted in Human Robots

#437689 GITAI Sending Autonomous Robot to Space ...

We’ve been keeping a close watch on GITAI since early last year—what caught our interest initially is the history of the company, which includes a bunch of folks who started in the JSK Lab at the University of Tokyo, won the DARPA Robotics Challenge Trials as SCHAFT, got swallowed by Google, narrowly avoided being swallowed by SoftBank, and are now designing robots that can work in space.

The GITAI YouTube channel has kept us more to less up to date on their progress so far, and GITAI has recently announced the next step in this effort: The deployment of one of their robots on board the International Space Station in 2021.

Photo: GITAI

GITAI’s S1 is a task-specific 8-degrees-of-freedom arm with an integrated sensing and computing system and 1-meter reach.

GITAI has been working on a variety of robots for space operations, the most sophisticated of which is a humanoid torso called G1, which is controlled through an immersive telepresence system. What will be launching into space next year is a more task-specific system called the S1, which is an 8-degrees-of-freedom arm with an integrated sensing and computing system that can be wall-mounted and has a 1-meter reach.

The S1 will be living on board a commercially funded, pressurized airlock-extension module called Bishop, developed by NanoRacks. Mounted on the inside of the Bishop module, the S1 will have access to a task board and a small assembly area, where it will demonstrate common crew intra-vehicular activity, or IVA—tasks like flipping switches, turning knobs, and managing cables. It’ll also do some in-space assembly, or ISA, attaching panels to create a solar array.

Here’s a demonstration of some task board activities, conducted on Earth in a mockup of Bishop:

GITAI says that “all operations conducted by the S1 GITAI robotic arm will be autonomous, followed by some teleoperations from Nanoracks’ in-house mission control.” This is interesting, because from what we’ve seen until now, GITAI has had a heavy emphasis on telepresence, with a human in the loop to get stuff done. As GITAI’s founder and CEO Sho Nakanose commented to us a year ago, “Telepresence robots have far better performance and can be made practical much quicker than autonomous robots, so first we are working on making telepresence robots practical.”

So what’s changed? “GITAI has been concentrating on teleoperations to demonstrate the dexterity of our robot, but now it’s time to show our capabilities to do the same this time with autonomy,” Nakanose told us last week. “In an environment with minimum communication latency, it would be preferable to operate a robot more with teleoperations to enhance the capability of the robot, since with the current technology level of AI, what a robot can do autonomously is very limited. However, in an environment where the latency becomes noticeable, it would become more efficient to have a mixture of autonomy and teleoperations depending on the application. Eventually, in an ideal world, a robot will operate almost fully autonomously with minimum human cognizance.”

“In an environment where the latency becomes noticeable, it would become more efficient to have a mixture of autonomy and teleoperations depending on the application. Eventually, in an ideal world, a robot will operate almost fully autonomously with minimum human cognizance.”
—Sho Nakanose, GITAI founder and CEO

Nakanose says that this mission will help GITAI to “acquire the skills, know-how, and experience necessary to prepare a robot to be ISS compatible, prov[ing] the maturity of our technology in the microgravity environment.” Success would mean conducting both IVA and ISA experiments as planned (autonomous and teleop for IVA, fully autonomous for ISA), which would be pretty awesome, but we’re told that GITAI has already received a research and development order for space robots from a private space company, and Nakanose expects that “by the mid-2020s, we will be able to show GITAI's robots working in space on an actual mission.”

NanoRacks is schedule to launch the Bishop module on SpaceX CRS-21 in November. The S1 will be launched separately in 2021, and a NASA astronaut will install the robot and then leave it alone to let it start demonstrating how work in space can be made both safer and cheaper once the humans have gotten out of the way. Continue reading

Posted in Human Robots