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#437745 Video Friday: Japan’s Giant Gundam ...

Posted on November 27, 2020 by Android

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
AUVSI EXPONENTIAL 2020 – October 5-8, 2020 – [Online Conference]
IROS 2020 – October 25-29, 2020 – Las Vegas, Nev., USA
ICSR 2020 – November 14-16, 2020 – Golden, Co., USA
Let us know if you have suggestions for next week, and enjoy today’s videos.

It’s coming together—literally! Japan’s giant Gundam appears nearly finished and ready for its first steps. In a recent video, Gundam Factory Yokohama, which is constructing the 18-meter-tall, 25-ton walking robot, provided an update on the project. The video shows the Gundam getting its head attached—after being blessed by Shinto priests.

In the video update, they say the project is “steadily progressing” and further details will be announced around the end of September.

[ Gundam Factory Yokohama ]

Creating robots with emotional personalities will transform the usability of robots in the real-world. As previous emotive social robots are mostly based on statically stable robots whose mobility is limited, this work develops an animation to real-world pipeline that enables dynamic bipedal robots that can twist, wiggle, and walk to behave with emotions.

So that’s where Cassie’s eyes go.

[ Berkeley ]

Now that the DARPA SubT Cave Circuit is all virtual, here’s a good reminder of how it’ll work.

[ SubT ]

Since July 20, anyone 11+ years of age must wear a mask in closed public places in France. This measure also is highly recommended in many European, African and Persian Gulf countries. To support businesses and public places, SoftBank Robotics Europe unveils a new feature with Pepper: AI Face Mask Detection.

[ Softbank ]

University of Michigan researchers are developing new origami inspired methods for designing, fabricating and actuating micro-robots using heat.These improvements will expand the mechanical capabilities of the tiny bots, allowing them to fold into more complex shapes.

[ University of Michigan ]

Suzumori Endo Lab, Tokyo Tech has created various types of IPMC robots. Those robots are fabricated by novel 3D fabrication methods.

[ Suzimori Endo Lab ]

The most explode-y of drones manages not to explode this time.

[ SpaceX ]

At Amazon, we’re constantly innovating to support our employees, customers, and communities as effectively as possible. As our fulfillment and delivery teams have been hard at work supplying customers with items during the pandemic, Amazon’s robotics team has been working behind the scenes to re-engineer bots and processes to increase safety in our fulfillment centers.

While some folks are able to do their jobs at home with just a laptop and internet connection, it’s not that simple for other employees at Amazon, including those who spend their days building and testing robots. Some engineers have turned their homes into R&D labs to continue building these new technologies to better serve our customers and employees. Their creativity and resourcefulness to keep our important programs going is inspiring.

[ Amazon ]

Australian Army soldiers from 2nd/14th Light Horse Regiment (Queensland Mounted Infantry) demonstrated the PD-100 Black Hornet Nano unmanned aircraft vehicle during a training exercise at Shoalwater Bay Training Area, Queensland, on 4 May 2018.

This robot has been around for a long time—maybe 10 years or more? It makes you wonder what the next generation will look like, and if they can manage to make it even smaller.

[ FLIR ]

Event-based cameras are bio-inspired vision sensors whose pixels work independently from each other and respond asynchronously to brightness changes, with microsecond resolution. Their advantages make it possible to tackle challenging scenarios in robotics, such as high-speed and high dynamic range scenes. We present a solution to the problem of visual odometry from the data acquired by a stereo event-based camera rig.

[ Paper ] via [ HKUST ]

Emys can help keep kindergarteners sitting still for a long time, which is not small feat!

[ Emys ]

Introducing the RoboMaster EP Core, an advanced educational robot that was built to take learning to the next level and provides an all-in-one solution for STEAM-based classrooms everywhere, offering AI and programming projects for students of all ages and experience levels.

[ DJI ]

This Dutch food company Heemskerk uses ABB robots to automate their order picking. Their new solution reduces the amount of time the fresh produce spends in the supply chain, extending its shelf life, minimizing wastage, and creating a more sustainable solution for the fresh food industry.

[ ABB ]

This week’s episode of Pass the Torque features NASA’s Satellite Servicing Projects Division (NExIS) Robotics Engineer, Zakiya Tomlinson.

[ NASA ]

Massachusetts has been challenging Silicon Valley as the robotics capital of the United States. They’re not winning, yet. But they’re catching up.

[ MassTech ]

San Francisco-based Formant is letting anyone remotely take its Spot robot for a walk. Watch The Robot Report editors, based in Boston, take Spot for a walk around Golden Gate Park.

You can apply for this experience through Formant at the link below.

[ Formant ] via [ TRR ]

Thanks Steve!

An Institute for Advanced Study Seminar on “Theoretical Machine Learning,” featuring Peter Stone from UT Austin.

For autonomous robots to operate in the open, dynamically changing world, they will need to be able to learn a robust set of skills from relatively little experience. This talk begins by introducing Grounded Simulation Learning as a way to bridge the so-called reality gap between simulators and the real world in order to enable transfer learning from simulation to a real robot. It then introduces two new algorithms for imitation learning from observation that enable a robot to mimic demonstrated skills from state-only trajectories, without any knowledge of the actions selected by the demonstrator. Connections to theoretical advances in off-policy reinforcement learning will be highlighted throughout.

[ IAS ] Continue reading →

Posted in Human Robots

#437741 CaseCrawler Adds Tiny Robotic Legs to ...

Posted on November 27, 2020 by Android

Most of us have a fairly rational expectation that if we put our cellphone down somewhere, it will stay in that place until we pick it up again. Normally, this is exactly what you’d want, but there are exceptions, like when you put your phone down in not quite the right spot on a wireless charging pad without noticing, or when you’re lying on the couch and your phone is juuust out of reach no matter how much you stretch.

Roboticists from the Biorobotics Laboratory at Seoul National University in South Korea have solved both of these problems, and many more besides, by developing a cellphone case with little robotic legs, endowing your phone with the ability to skitter around autonomously. And unlike most of the phone-robot hybrids we’ve seen in the past, this one actually does look like a legit case for your phone.

CaseCrawler is much chunkier than a form-fitting case, but it’s not offensively bigger than one of those chunky battery cases. It’s only 24 millimeters thick (excluding the motor housing), and the total weight is just under 82 grams. Keep in mind that this case is in fact an entire robot, and also not at all optimized for being an actual phone case, so it’s easy to imagine how it could get a lot more svelte—for example, it currently includes a small battery that would be unnecessary if it instead tapped into the phone for power.

The technology inside is pretty amazing, since it involves legs that can retract all the way flat while also supporting a significant amount of weight. The legs work sort of like your legs do, in that there’s a knee joint that can only bend one way. To move the robot forward, a linkage (attached to a motor through a gearbox) pushes the leg back against the ground, as the knee joint keeps the leg straight. On the return stroke, the joint allows the leg to fold, making it compliant so that it doesn’t exert force on the ground. The transmission that sends power from the gearbox to the legs is just 1.5-millimeter thick, but this incredibly thin and lightweight mechanical structure is quite powerful. A non-phone case version of the robot, weighing about 23 g, is able to crawl at 21 centimeters per second while carrying a payload of just over 300 g. That’s more than 13 times its body weight.

The researchers plan on exploring how robots like these could make other objects movable that would otherwise not be. They’d also like to add some autonomy, which (at least for the phone case version) could be as straightforward as leveraging the existing sensors on the phone. And as to when you might be able to buy one of these—we’ll keep you updated, but the good news is that it seems to be fundamentally inexpensive enough that it may actually crawl out of the lab one day.

“CaseCrawler: A Lightweight and Low-Profile Crawling Phone Case Robot,” by Jongeun Lee, Gwang-Pil Jung, Sang-Min Baek, Soo-Hwan Chae, Sojung Yim, Woongbae Kim, and Kyu-Jin Cho from Seoul National University, appears in the October issue of IEEE Robotics and Automation Letters.

< Back to IEEE Journal Watch Continue reading →

Posted in Human Robots

#437723 Minuscule RoBeetle Turns Liquid Methanol ...

Posted on November 26, 2020 by Android

It’s no secret that one of the most significant constraints on robots is power. Most robots need lots of it, and it has to come from somewhere, with that somewhere usually being a battery because there simply aren’t many other good options. Batteries, however, are famous for having poor energy density, and the smaller your robot is, the more of a problem this becomes. And the issue with batteries goes beyond the battery itself, but also carries over into all the other components that it takes to turn the stored energy into useful work, which again is a particular problem for small-scale robots.

In a paper published this week in Science Robotics, researchers from the University of Southern California, in Los Angeles, demonstrate RoBeetle, an 88-milligram four legged robot that runs entirely on methanol, a power-dense liquid fuel. Without any electronics at all, it uses an exceptionally clever bit of mechanical autonomy to convert methanol vapor directly into forward motion, one millimeter-long step at a time.

It’s not entirely clear from the video how the robot actually works, so let’s go through how it’s put together, and then look at the actuation cycle.

Image: Science Robotics

RoBeetle (A) uses a methanol-based actuation mechanism (B). The robot’s body (C) includes the fuel tank subassembly (D), a tank lid, transmission, and sliding shutter (E), bottom side of the sliding shutter (F), nickel-titanium-platinum composite wire and leaf spring (G), and front legs and hind legs with bioinspired backward-oriented claws (H).

The body of RoBeetle is a boxy fuel tank that you can fill with methanol by poking a syringe through a fuel inlet hole. It’s a quadruped, more or less, with fixed hind legs and two front legs attached to a single transmission that moves them both at once in a sort of rocking forward and up followed by backward and down motion. The transmission is hooked up to a leaf spring that’s tensioned to always pull the legs backward, such that when the robot isn’t being actuated, the spring and transmission keep its front legs more or less vertical and allow the robot to stand. Those horns are primarily there to hold the leaf spring in place, but they’ve got little hooks that can carry stuff, too.

The actuator itself is a nickel-titanium (NiTi) shape-memory alloy (SMA), which is just a wire that gets longer when it heats up and then shrinks back down when it cools. SMAs are fairly common and used for all kinds of things, but what makes this particular SMA a little different is that it’s been messily coated with platinum. The “messily” part is important for a reason that we’ll get to in just a second.

The way that the sliding vent is attached to the transmission is the really clever bit about this robot, because it means that the motion of the wire itself is used to modulate the flow of fuel through a purely mechanical system. Essentially, it’s an actuator and a sensor at the same time.

One end of the SMA wire is attached to the middle of the leaf spring, while the other end runs above the back of the robot where it’s stapled to an anchor block on the robot’s rear end. With the SMA wire hooked up but not actuated (i.e., cold rather than warm), it’s short enough that the leaf spring gets pulled back, rocking the legs forward and up. The last component is embedded in the robot’s back, right along the spine and directly underneath the SMA actuator. It’s a sliding vent attached to the transmission, so that the vent is open when the SMA wire is cold and the leaf spring is pulled back, and closed when the SMA wire is warm and the leaf spring is relaxed. The way that the sliding vent is attached to the transmission is the really clever bit about this robot, because it means that the motion of the wire itself is used to modulate the flow of fuel through a purely mechanical system. Essentially, it’s an actuator and a sensor at the same time.

The actuation cycle that causes the robot to walk begins with a full fuel tank and a cold SMA wire. There’s tension on the leaf spring, pulling the transmission back and rocking the legs forward and upward. The transmission also pulls the sliding vent into the open position, allowing methanol vapor to escape up out of the fuel tank and into the air, where it wafts past the SMA wire that runs directly above the vent.

The platinum facilitates a reaction of the methanol (CH3OH) with oxygen in the air (combustion, although not the dramatic flaming and explosive kind) to generate a couple of water molecules and some carbon dioxide plus a bunch of heat, and this is where the messy platinum coating is important, because messy means lots of surface area for the platinum to interact with as much methanol as possible. In just a second or two the temperature of the SMA wire skyrockets from 50 to 100 ºC and it expands, allowing the leaf spring about 0.1 mm of slack. As the leaf spring relaxes, the transmission moves the legs backwards and downwards, and the robot pulls itself forward about 1.2 mm. At the same time, the transmission is closing off the sliding vent, cutting off the supply of methanol vapor. Without the vapor reacting with the platinum and generating heat, in about a second and a half, the SMA wire cools down. As it does, it shrinks, pulling on the leaf spring and starting the cycle over again. Top speed is 0.76 mm/s (0.05 body-lengths per second).

An interesting environmental effect is that the speed of the robot can be enhanced by a gentle breeze. This is because air moving over the SMA wire cools it down a bit faster while also blowing away any residual methanol from around the vents, shutting down the reaction more completely. RoBeetle can carry more than its own body weight in fuel, and it takes approximately 155 minutes for a full tank of methanol to completely evaporate. It’s worth noting that despite the very high energy density of methanol, this is actually a stupendously inefficient way of powering a robot, with an estimated end-to-end efficiency of just 0.48 percent. Not 48 percent, mind you, but 0.48 percent, while in general, powering SMAs with electricity is much more efficient.

However, you have to look at the entire system that would be necessary to deliver that electricity, and for a robot as small as RoBeetle, the researchers say that it’s basically impossible. The lightest commercially available battery and power supply that would deliver enough juice to heat up an SMA actuator weighs about 800 mg, nearly 10 times the total weight of RoBeetle itself. From that perspective, RoBeetle’s efficiency is actually pretty good.

Image: A. Kitterman/Science Robotics; adapted from R.L.T./MIT

Comparison of various untethered microrobots and bioinspired soft robots that use different power and actuation strategies.

There are some other downsides to RoBeetle we should mention—it can only move forwards, not backwards, and it can’t steer. Its speed isn’t adjustable, and once it starts walking, it’ll walk until it either breaks or runs out of fuel. The researchers have some ideas about the speed, at least, pointing out that increasing the speed of fuel delivery by using pressurized liquid fuels like butane or propane would increase the actuator output frequency. And the frequency, amplitude, and efficiency of the SMAs themselves can be massively increased “by arranging multiple fiber-like thin artificial muscles in hierarchical configurations similar to those observed in sarcomere-based animal muscle,” making RoBeetle even more beetle-like.

As for sensing, RoBeetle’s 230-mg payload is enough to carry passive sensors, but getting those sensors to usefully interact with the robot itself to enable any kind of autonomy remains a challenge. Mechanically intelligence is certainly possible, though, and we can imagine RoBeetle adopting some of the same sorts of systems that have been proposed for the clockwork rover that JPL wants to use for Venus exploration. The researchers also mention how RoBeetle could potentially serve as a model for microbots capable of aerial locomotion, which is something we’d very much like to see.

“An 88-milligram insect-scale autonomous crawling robot driven by a catalytic artificial muscle,” by Xiufeng Yang, Longlong Chang, and Néstor O. Pérez-Arancibia from University of Southern California, in Los Angeles, was published in Science Robotics. Continue reading →

Posted in Human Robots

#437716 Robotic Tank Is Designed to Crawl ...

Posted on November 26, 2020 by Android

Let’s talk about bowels! Most of us have them, most of us use them a lot, and like anything that gets used a lot, they eventually need to get checked out to help make sure that everything will keep working the way it should for as long as you need it to. Generally, this means a colonoscopy, and while there are other ways of investigating what’s going on in your gut, a camera on a flexible tube is still “the gold-standard method of diagnosis and intervention,” according to some robotics researchers who want to change that up a bit.

The University of Colorado’s Advanced Medical Technologies Lab has been working on a tank robot called Endoculus that’s able to actively drive itself through your intestines, rather than being shoved. The good news is that it’s very small, and the bad news is that it’s probably not as small as you’d like it to be.

The reason why a robot like Endoculus is necessary (or at least a good idea) is that trying to stuff a semi-rigid endoscopy tube into the semi-floppy tube that is your intestine doesn’t always go smoothly. Sometimes, the tip of the endoscopy tube can get stuck, and as more tube is fed in, it causes the intestine to distend, which best case is painful and worst case can cause serious internal injuries. One way of solving this is with swallowable camera pills, but those don’t help you with tasks like taking tissue samples. A self-propelled system like Endoculus could reduce risk while also making the procedure faster and cheaper.

Image: Advanced Medical Technologies Lab/University of Colorado

The researchers say that while the width of Endoculus is larger than a traditional endoscope, the device would require “minimal distention during use” and would “not cause pain or harm to the patient.” Future versions of the robot, they add, will “yield a smaller footprint.”

Endoculus gets around with four sets of treads, angled to provide better traction against the curved walls of your gut. The treads are micropillared, or covered with small nubs, which helps them deal with all your “slippery colon mucosa.” Designing the robot was particularly tricky because of the severe constraints on the overall size of the device, which is just 3 centimeters wide and 2.3 cm high. In order to cram the two motors required for full control, they had to be arranged parallel to the treads, resulting in a fairly complex system of 3D-printed worm gears. And to make the robot actually useful, it includes a camera, LED lights, tubes for injecting air and water, and a tool port that can accommodate endoscopy instruments like forceps and snares to retrieve tissue samples.

So far, Endoculus has spent some time inside of a live pig, although it wasn’t able to get that far since pig intestines are smaller than human intestines, and because apparently the pig intestine is spiraled somehow. The pig (and the robot) both came out fine. A (presumably different) pig then provided some intestine that was expanded to human-intestine size, inside of which Endoculus did much better, and was able to zip along at up to 40 millimeters per second without causing any damage. Personally, I’m not sure I’d want a robot to explore my intestine at a speed much higher than that.

The next step with Endoculus is to add some autonomy, which means figuring out how to do localization and mapping using the robot’s onboard camera and IMU. And then of course someone has to be the first human to experience Endoculus directly, which I’d totally volunteer for except the research team is in Colorado and I’m not. Sorry!

“Novel Optimization-Based Design and Surgical Evaluation of a Treaded Robotic Capsule Colonoscope,” by Gregory A. Formosa, J. Micah Prendergast, Steven A. Edmundowicz, and Mark E. Rentschler, from the University of Colorado, was presented at ICRA 2020.

< Back to IEEE Journal Watch Continue reading →

Posted in Human Robots

#437709 iRobot Announces Major Software Update, ...

Posted on November 25, 2020 by Android

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