Recently Yujin Robot launched a new 3D LiDAR for indoor service robot, AGVs/AMRs and smart factory. The YRL3 series is a line of precise laser sensors for vertical and horizontal scanning to detect environments or objects. The Yujin Robot YRL3 series LiDAR is designed for indoor applications and utilizes an innovative 3D scanning LiDAR for a 270°(Horizontal) x 90°(vertical) dynamic field of view as a single channel. The fundamental principle is based on direct ToF (Time of Flight) and designed to measure distances towards surroundings. YRL3 collect useful data including ranges, angles, intensities and Cartesian coordinates (x,y,z). Real-time vertical right-angle adjustment is possible and supports powerful S/W package for autonomous driving devices.
“In recent years, our product lineup expanded to include models for the Fourth Industrial Revolution,” shares the marketing team of Yujin Robot. These models namely are Kobuki, the ROS reference research robot platform used by robotics research labs around the world, the Yujin LiDAR range-finding scanning sensor for LiDAR-based autonomous driving, AMS solution (Autonomous Mobility Solution) for customized autonomous driving. The company continues to push the boundaries of robotics and artificial intelligence, developing game-changing autonomous solutions that give companies around the world an edge over the competition.
Yesterday, the Toyota Research Institute (TRI)showed off some of the projects that it’s been working on recently, including a ceiling-mounted robot that could one day help us with household chores. That system is just one example of how TRI envisions the future of robotics and artificial intelligence. As TRI CEO Gill Pratt told us, the company is focusing on robotics and AI technology for “amplifying, rather than replacing, human beings.” In other words, Toyota wants to develop robots not for convenience or to do our jobs for us, but rather to allow people to continue to live and work independently even as we age.
To better understand Toyota’s vision of robotics 15 to 20 years from now, it’s worth watching the 20-minute video below, which depicts various scenarios “where the application of robotic capabilities is enabling members of an aging society to live full and independent lives in spite of the challenges that getting older brings.” It’s a long video, but it helps explains TRI’s perspective on how robots will collaborate with humans in our daily lives over the next couple of decades.
Those are some interesting conceptual telepresence-controlled bipeds they’ve got running around in that video, right?
For more details, we sent TRI some questions on how it plans to go from concepts like the ones shown in the video to real products that can be deployed in human environments. Below are answers from TRI CEO Gill Pratt, who is also chief scientist for Toyota Motor Corp.; Steffi Paepcke, senior UX designer at TRI; and Max Bajracharya, VP of robotics at TRI.
IEEE Spectrum: TRI seems to have a more explicit focus on eventual commercialization than most of the robotics research that we cover. At what point TRI starts to think about things like reliability and cost?
Gill Pratt: It’s a really interesting question, because the normal way to think about this would be to say, well, both reliability and cost are product development tasks. But actually, we need to think about it at the earliest possible stage with research as well. The hardware that we use in the laboratory for doing experiments, we don’t worry about cost there, or not nearly as much as you’d worry about for a product. However, in terms of what research we do, we very much have to think about, is it possible (if the research is successful) for it to end up in a product that has a reasonable cost. Because if a customer can’t afford what we come up with, maybe it has some academic value but it’s not actually going to make a difference in their quality of life in the real world. So we think about cost very much from the beginning.
The same is true with reliability. Right now, we’re working very hard to make our control techniques robust to wide variations in the environment. For instance, in work that Russ Tedrake is doing with manipulating dishes in a sink and a dishwasher, both in physical testing and in simulation, we’re doing thousands and now millions of different experiments to make sure that we can handle the edge cases and it works over a very wide range of conditions.
A tremendous amount of work that we do is trying to bring robotics out of the age of doing demonstrations. There’s been a history of robotics where for some time, things have not been reliable, so we’d catch the robot succeeding just once and then show that video to the world, and people would get the mis-impression that it worked all of the time. Some researchers have been very good about showing the blooper reel too, to show that some of the time, robots don’t work.
In the spirit of sharing things that didn’t work, can you tell us a bit about some of the robots that TRI has had under development that didn’t make it into the demo yesterday because they were abandoned along the way?
Steffi Paepcke: We’re really looking at how we can connect people; it can be hard to stay in touch and see our loved ones as much as we would like to. There have been a few prototypes that we’ve worked on that had to be put on the shelf, at least for the time being. We were exploring how to use light so that people could be ambiently aware of one another across distances. I was very excited about that—the internal name was “glowing orb.” For a variety of reasons, it didn’t work out, but it was really fascinating to investigate different modalities for keeping in touch.
Another prototype we worked on—we found through our research that grocery shopping is obviously an important part of life, and for a lot of older adults, it’s not necessarily the right answer to always have groceries delivered. Getting up and getting out of the house keeps you physically active, and a lot of people prefer to continue doing it themselves. But it can be challenging, especially if you’re purchasing heavy items that you need to transport. We had a prototype that assisted with grocery shopping, but when we pivoted our focus to Japan, we found that the inside of a Japanese home really needs to stay inside, and the outside needs to stay outside, so a robot that traverses both domains is probably not the right fit for a Japanese audience, and those were some really valuable lessons for us.
I love that TRI is exploring things like the gantry robot both in terms of near-term research and as part of its long-term vision, but is a robot like this actually worth pursuing? Or more generally, what’s the right way to compromise between making an environment robot friendly, and asking humans to make changes to their homes?
Max Bajracharya: We think a lot about the problems that we’re trying to address in a holistic way. We don’t want to just give people a robot, and assume that they’re not going to change anything about their lifestyle. We have a lot of evidence from people who use automated vacuum cleaners that people will adapt to the tools you give them, and they’ll change their lifestyle. So we want to think about what is that trade between changing the environment, and giving people robotic assistance and tools.
We certainly think that there are ways to make the gantry system plausible. The one you saw today is obviously a prototype and does require significant infrastructure. If we’re going to retrofit a home, that isn’t going to be the way to do it. But we still feel like we’re very much in the prototype phase, where we’re trying to understand whether this is worth it to be able to bypass navigation challenges, and coming up with the pros and cons of the gantry system. We’re evaluating whether we think this is the right approach to solving the problem.
To what extent do you think humans should be either directly or indirectly in the loop with home and service robots?
Bajracharya: Our goal is to amplify people, so achieving this is going to require robots to be in a loop with people in some form. One thing we have learned is that using people in a slow loop with robots, such as teaching them or helping them when they make mistakes, gives a robot an important advantage over one that has to do everything perfectly 100 percent of the time. In unstructured human environments, robots are going to encounter corner cases, and are going to need to learn to adapt. People will likely play an important role in helping the robots learn.
Over the last several years, Toyota has been putting more muscle into forward-looking robotics research than just about anyone. In addition to the Toyota Research Institute (TRI), there’s that massive 175-acre robot-powered city of the future that Toyota still plans to build next to Mount Fuji. Even Toyota itself acknowledges that it might be crazy, but that’s just how they roll—as TRI CEO Gill Pratt told me a while back, when Toyota decides to do something, they really do go all-in on it.
TRI has been focusing heavily on home robots, which is reflective of the long-term nature of what TRI is trying to do, because home robots are both the place where we’ll need robots the most at the same time as they’re the place where it’s going to be hardest to deploy them. The unpredictable nature of homes, and the fact that homes tend to have squishy fragile people in them, are robot-unfriendly characteristics, but as the population continues to age (an increasingly acute problem in Japan), homes offer an enormous amount of potential for helping us maintain our independence.
Today, Toyota is showing off some of the research that it’s been working on recently, in the form of a virtual reality presentation in lieu of an in-person press event. For journalists, TRI pre-loaded the recording onto a VR headset, which was FedEx’ed to my house.You can watch the entire 40-minute presentation in 360 video on YouTube (or in VR if you have a headset of your own), but if you don’t watch the whole thing, you should at least check out the full-on GLaDOS (with arms) that TRI thinks belongs in your home.
iRobot has released several new robots over the last few years, including the i7 and s9 vacuums. Both of these models are very fancy and very capable, packed with innovative and useful features that we’ve been impressed by. They’re both also quite expensive—with dirt docks included, you’re looking at US $800 for the i7+, and a whopping $1,100 for the s9+. You can knock a couple hundred bucks off of those prices if you don’t want the docks, but still, these vacuums are absolutely luxury items.
If you just want something that’ll do some vacuuming so that you don’t have to, iRobot has recently announced a new Roomba option. The Roomba i3 is iRobot’s new low to midrange vacuum, starting at $400. It’s not nearly as smart as the i7 or the s9, but it can navigate (sort of) and make maps (sort of) and do some basic smart home integration. If that sounds like all you need, the i3 could be the robot vacuum for you.
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 their 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.
iRobot has been on a major push into education robots recently. They acquired Root Robotics in 2019, and earlier this year, launched an online simulator and associated curriculum designed to work in tandem with physical Root robots. The original Root was intended to be a classroom robot, with one of its key features being the ability to stick to (and operate on) magnetic virtual surfaces, like whiteboards. And as a classroom robot, at $200, it’s relatively affordable, if you can buy one or two and have groups of kids share them.
For kids who are more focused on learning at home, though, $200 is a lot for a robot that doesn’t even keep your floors clean. And as nice as it is to have a free simulator, any kid will tell you that it’s way cooler to have a real robot to mess around with. Today, iRobot is announcing a new version of Root that’s been redesigned for home use, with a $129 price that makes it significantly more accessible to folks outside of the classroom.
Robots! Robots! Robots! This collection of fun activity sheets for kids is a perfect introduction to the amazing world of robots.
The activities are meant to be intuitive and clear, with little direction needed so that it’s easy for most kids to do the work independently. We think these activities can be enjoyed by kids age 6 to 12, though older kids (and adults!) may want to explore some of them, too.
The sheets can be printed out or done on a computer or tablet. Some activities require that kids use IEEE Spectrum’s Robots Guide to learn more about some of the robots; other activities, however, don’t require access to the site.
This material was created by Spectrum and is free. If you’d like to support this project, please consider making a donation through the IEEE Foundation. We’re regularly updating the Robots Guide, and hope to keep improving the activity sheets too. Have fun with robots!
Over the last 10 years, the PR2 has helped roboticists make an enormous amount of progress in mobile manipulation over a relatively short time. I mean, it’s been a decade already, but still—robots are hard, and giving a bunch of smart people access to a capable platform where they didn’t have to worry about hardware and could instead focus on doing interesting and useful things helped to establish a precedent for robotics research going forward.
Unfortunately, not everyone can afford an enormous US $400,000 robot, and even if they could, PR2s are getting very close to the end of their lives. There are other mobile manipulators out there taking the place of the PR2, but so far, size and cost have largely restricted them to research labs. Lots of good research is being done, but it’s getting to the point where folks want to take the next step: making mobile manipulators real-world useful.
Today, a company called Hello Robot is announcing a new mobile manipulator called the Stretch RE1. Hello Robot is led by Aaron Edsinger and Charlie Kemp, and by combining decades of experience in industry and academia they’ve managed to come up with a robot that’s small, lightweight, capable, and affordable, all at the same time. For now, it’s a research platform, but eventually, its creators hope that it will be able to come into our homes and take care of us when we need it to.
A few weeks ago, we asked folks on Twitter, Facebook, and LinkedIn to share photos and videos showing how they’ve been adapting to the closures of research labs, classrooms, and businesses by taking their robots home with them to continue their work as best they can. We got dozens of responses (more than we could possibly include in just one post!), but here are 15 that we thought were particularly creative or amusing.
And if any of these pictures and videos inspire you to share your own story, please email us ([email protected]) with a picture or video and a brief description about how you and your robot from work have been making things happen in your home instead.
The first generation of social home robots (like the first generation of many other new applications of technology) were not particularly successful. A series of very high valuations followed by mediocre sales and reviews leading to several company shutdowns has made it much more challenging to develop in this space. And that’s not necessarily a bad thing, if we’re honest— it’s become clear that social home robots are very, very difficult to get right, and any company who wants to make one at this point needs to have both the technical capability and (more importantly) a long-term business case that’s more comprehensive than just making a robot into a part of the family or a best friend.
Today, a social robotics startup called Embodied is launching a new robot called Moxie (no relation to this or this), a social companion for children aged 6ish to 9ish “designed to help promote social, emotional and cognitive development through everyday play-based learning and captivating content.” In some ways, it’s like all the other social robots we’ve seen in the past, but in others, it’s different enough that it could find success— especially right now, when both kids and parents are in need of some extra help.
For the last decade-ish, EPFL’s Roombots have been modularizing their way towards becoming the only piece of furniture you’ll ever need. These little squarish roundish robotics modules, which can move around and latch onto each other, can collaboratively form chairs, tables, or whatever else you need or want. The idea is that you’d invest in a pile of Roombots, the pile size being proportional to the number of people and animals in your house, and then whatever bits of furniture you desire would be dynamically created (and then “destroyed”) through the intelligent and autonomous cooperation Roombots pile on an as-needed basis.
Roombots are a very compelling idea, especially for those of us who have small apartments. Like, I have a dining room table and four chairs. If I want to have more than a couple people over for dinner, they’d better bring their own chairs, because I don’t have anywhere for them to sit. If my furniture was Roombots, though, my bed could just disassemble itself to make more chairs when I needed them. Or, I could store a bunch of extra Roombot modules in my closet, and bring them out when needed.
In a new Roombots paper, researchers from EPFL’s Biorobotics Laboratory, led by Professor Auke Ijspeert, have demonstrated some practical (although still very research-y) swarm transformations, while also experimenting with how Roombots can interact with existing furniture to give it new capabilities—chairs that follow you, chairs that flee from you, and tables that can pick objects up off the floor.
This article was originally published on LinkedIn. The views expressed here are solely those of the author and do not represent positions of IEEE Spectrum or the IEEE.
Build a rover, send it to the Moon, sell the movie rights.
That was our first business model at iRobot. Way back in 1990. We thought it would be how we’d first change the world. It’s ironic, of course, that through that model, changing the world meant sending a robot to another one. Sadly, that business model failed. And it wouldn’t be our last failed business model. Not by a long shot.
Why? Because changing the world through robots, it turns out, is no easy task.
Perhaps the biggest challenge back when we started in 1990 was that there existed no rule book on how to do it. There weren’t many robots, let alone robot companies, let alone any kind of robot industry. We would have to build it. All of it.
Walking that path meant being comfortable with ambiguity, and comfortable with the knowledge that not everything we tried was going to work–at least not in the way we originally conceived. It was and continues to be the cost of inventing the future.
But walking that trying path also meant learning from our mistakes, dusting ourselves off, trying again, and eventually, yes, doing what we set out to do: Change the world through robots.
We’ve learned so much along the way–what have we learned in our 30-year journey building the robot industry?
Robots are hard
I’ve said it before, and I’ll say it again: When we first started iRobot we had to invent every element of the robot. Spatial navigation was a robot problem, voice recognition was a robot problem, machine vision was a robot problem, just to name a few. Back then, no one else had set out to solve these hard problems. Because so many of these problems existed, the robot industry, if it could be called that, moved in anti-dog years. Fortunately, times have changed and the ecosystem around the technologies that make robots possible is much richer… But back then… it was just us.
But even today, with a much larger ecosystem of bright minds solving for the hard tech problems, getting a robot to work successfully still means getting just the right mix of mechanical, electrical, and software engineering, connectivity, and data science into a robot form factor that people trust and want to invite into their home.
Speaking of trust, therein lied another challenge. Even when we did invent a robot that worked extraordinarily well–Roomba–consumers simply didn’t believe a robot could do what we said Roomba was capable of. It turns out that the principal objection to purchasing a robot for much of the last 30 years is a lack of belief that it could possibly work.
But that’s not all: Even when you build a robot right, you can still somehow build it wrong. We experienced this with Roomba. We built it to match the reliability standards of European upright vacuums, something of which we were very proud. Of course, we didn’t anticipate that our customers would run their Roomba once per day, rather than the once per week average the European standard set. And as the first generation of Roomba robots broke down two years ahead of schedule, we learned that reverse logistics, great customer service, and a generous return policy were a very important part of a good robot–as was the realization that we couldn’t compare usage to whatever traditional means of action a good robot might take the place of.
And yet while building a robot that was durable, that people wanted and trusted was hard enough, 30 years building robots has also taught us that…
Good business models are harder to build than good robots
Let’s state this one right off the bat: For a long time the robot industry was unfundable. Why? Because no robot company had a business model worth funding. It turns out that a business model is as important as the tech, but much more rarely found in a robot company. And for a long time we were no exception: We tried 14 business models before we arrived at one that sustainably worked.
But the tenuous nature of our business models did teach us the value of extending the runway for our business until we found one that worked. And how does one extend the runway most effectively? By managing risk.
It’s one of the great misunderstandings of entrepreneurship–that great entrepreneurs are risk takers. Great entrepreneurs are not great risk takers… they’re great risk managers. And this was something we at iRobot were and are exceptionally good at.
How did we manage risk early on? Through partnerships. The kind of partnership we looked for were ones in which there was a big company–one that had a lot of money, a channel to the marketplace, and knowledge of that marketplace, but for whatever reason lacked belief that they themselves were innovative. We were a small company with no money, but believed ourselves to have cool technology, and be highly capable of innovation.
What we’d do was give our partner, the big company, absolute control. By doing this, it allowed us to say that since they could cancel the partnership at any time, we needed them to cover our costs… which they did. But we also didn’t ask them to pay us profit upfront. By not having the pay profit upfront, it makes obvious that we’re sharing the value that the partnership would ultimately create, and in a worst-case scenario for our partner, if the partnership didn’t result in a successful product, they got very inexpensive high-quality research.
This “asymmetric strategic partnership” approach not only provided the funds needed to sustain our business when we didn’t have a sustainable business model–the “failure” of those partnerships actually led to our ultimate success. Why? Because…
Innovation and failure come hand-in-hand
While this is far from a groundbreaking realization, its applicability to iRobot is quite unique. Because for us to become successful, it turns out that we had to learn the lessons from failing to earn royalties on robot toys (business model #3), failing to license technology for industrial floor-cleaning robots (business model #8), and failing to sell land mine clearance robots (business model #11).
Why? Because #3 taught us to manufacture at scale, #8 taught us how to clean floors, and #11 taught us how to navigate and cover large spaces. All of which gave us the knowledge and capability to build… Roomba.
Yes, you can change the world through robots
We did. In more ways the one. We changed the world by eliminating the need for people to vacuum the house themselves. By IPOing, we showed that a robotics company could be successful–which gave investors more reason to put money into robotics companies around the world.
But perhaps the most important way we’ve succeeded in changing the world is by making robots a daily reality for it. And how do we know that robots are now a reality? Because for the better part of the first 30 years of iRobot, what people said to me about robots–and Roomba specifically–was, “I can’t believe it actually works.”
But now, the question they ask me is, “Why can’t robots do more?”
It is a great question. And that is what the next 30 years of iRobot will be about.
Colin Angle is chairman of the board, chief executive officer, and founder of iRobot. Celebrating its 30th year, iRobot has grown from an MIT startup to become a global leader in consumer robots, with more than 30 million sold worldwide. You can follow him on Twitter at @ColinAngle.
This is a guest post. The views expressed here are solely those of the author and do not represent positions of IEEE Spectrum or the IEEE.
Honda Research Institute’s (HRI) experimental social robot Haru was first introduced at the ACM/IEEE Human Robot Interaction conference in 20181. The robot is designed as a platform to investigate social presence and emotional and empathetic engagement for long-term human interaction. Envisioned as a multimodal communicative agent, Haru interacts through nonverbal sounds (paralanguage), eye, face, and body movements (kinesics), and voice (language). While some of Haru’s features connect it to a long lineage of social robots, others distinguish it and suggest new opportunities for human-robot interaction.
Haru is currently in its first iteration, with plans underway for future development. Current research with Haru is conducted with core partners of the Socially Intelligent Robotics Consortium (SIRC), described in more detail below, and it concentrates on its potential to communicate across the previously mentioned three-way modality (language, paralanguage, and kinesics). Long term, we hope Haru will drive research into robots as a new form of companion species and as a platform for creative content.
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!):
When Anki abruptly shut down in April of last year, things looked bleak for Vector, Cozmo, and the Overdrive little racing cars. Usually, abrupt shutdowns don’t end well, with assets and intellectual property getting liquidated and effectively disappearing forever. Despite some vague promises (more like hopes, really) from Anki at the time that their cloud-dependent robots would continue to operate, it was pretty clear that Anki’s robots wouldn’t have much of a future—at best, they’d continue to work only as long as there was money to support the cloud servers that gave them their spark of life.
A few weeks ago, The Robot Report reported that Anki’s intellectual property (patents, trademarks, and data) was acquired by Digital Dream Labs, an education tech startup based in Pittsburgh. Over the weekend, a new post on the Vector Kickstarter page (the campaign happened in 2018) from Digital Dream Labs CEO Jacob Hanchar announced that not only will Vector’s cloud servers keep running indefinitely, but that the next few months will see a new Kickstarter to add new features and future-proofing to Vectors everywhere.
Welcome to the eighth edition of IEEE Spectrum’s Robot Gift Guide!
This year we’re featuring 15 robotic products that we think will make fantastic holiday gifts. As always, we tried to include a broad range of robot types and prices, focusing mostly on items released this year. (A reminder: While we provide links to places where you can buy these items, we’re not endorsing any in particular, and a little bit of research may result in better deals.)
If you need even more robot gift ideas, take a look at our past guides: 2018, 2017,2016, 2015, 2014, 2013, and 2012. Some of those robots are still great choices and might be way cheaper now than when we first posted about them. And if you have suggestions that you’d like to share, post a comment below to help the rest of us find the perfect robot gift.
By the time the crowdfunding campaign launched in August, the delivery date had slipped again, to September 2020, even as Blue Frog attempted to draw investors by estimating that sales of Buddy would “increase from 2000 robots in 2020 to 20,000 in 2023.” Blue Frog’s most recent communication with backers, in September, mentions a new CTO and a North American office, but does little to reassure backers of Buddy that they’ll ever be receiving their robot.
Backers of the robot are understandably concerned about the future of Buddy, so we sent a series of questions to the founder and CEO of Blue Frog Robotics, Rodolphe Hasselvander.
Developing robots for the home is still a challenge, especially if you want those robots to interact with people and help them do practical, useful things. However, the potential markets for home robots are huge, and one of the most compelling markets is for home robots that can assist humans who need them. Today, Labrador Systems, a startup based in California, is announcing a pre-seed funding round of $2 million (led by SOSV’s hardware accelerator HAX with participation from Amazon’s Alexa Fund and iRobot Ventures, among others) with the goal of expanding development and conducting pilot studies of “a new [assistive robot] platform for supporting home health.”
The recent high profile failures of some homesocialrobots (and the companies behind them) have made it even more challenging than it was before to develop robots in that space. And it was challenging enough to begin with—making a robot that can autonomous interact with random humans in their homes over a long period of time for a price that people can afford is extraordinarily difficult. However, the massive amount of initial interest in robots like Jibo, Kuri, Vector, and Buddy prove that people do want these things, or at least think they do, and while that’s the case, there’s incentive for other companies to give social home robots a try.
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