Tag Archives: real

#435765 The Four Converging Technologies Giving ...

How each of us sees the world is about to change dramatically.

For all of human history, the experience of looking at the world was roughly the same for everyone. But boundaries between the digital and physical are beginning to fade.

The world around us is gaining layer upon layer of digitized, virtually overlaid information—making it rich, meaningful, and interactive. As a result, our respective experiences of the same environment are becoming vastly different, personalized to our goals, dreams, and desires.

Welcome to Web 3.0, or the Spatial Web. In version 1.0, static documents and read-only interactions limited the internet to one-way exchanges. Web 2.0 provided quite an upgrade, introducing multimedia content, interactive web pages, and participatory social media. Yet, all this was still mediated by two-dimensional screens.

Today, we are witnessing the rise of Web 3.0, riding the convergence of high-bandwidth 5G connectivity, rapidly evolving AR eyewear, an emerging trillion-sensor economy, and powerful artificial intelligence.

As a result, we will soon be able to superimpose digital information atop any physical surrounding—freeing our eyes from the tyranny of the screen, immersing us in smart environments, and making our world endlessly dynamic.

In the third post of our five-part series on augmented reality, we will explore the convergence of AR, AI, sensors, and blockchain and dive into the implications through a key use case in manufacturing.

A Tale of Convergence
Let’s deconstruct everything beneath the sleek AR display.

It all begins with graphics processing units (GPUs)—electric circuits that perform rapid calculations to render images. (GPUs can be found in mobile phones, game consoles, and computers.)

However, because AR requires such extensive computing power, single GPUs will not suffice. Instead, blockchain can now enable distributed GPU processing power, and blockchains specifically dedicated to AR holographic processing are on the rise.

Next up, cameras and sensors will aggregate real-time data from any environment to seamlessly integrate physical and virtual worlds. Meanwhile, body-tracking sensors are critical for aligning a user’s self-rendering in AR with a virtually enhanced environment. Depth sensors then provide data for 3D spatial maps, while cameras absorb more surface-level, detailed visual input. In some cases, sensors might even collect biometric data, such as heart rate and brain activity, to incorporate health-related feedback in our everyday AR interfaces and personal recommendation engines.

The next step in the pipeline involves none other than AI. Processing enormous volumes of data instantaneously, embedded AI algorithms will power customized AR experiences in everything from artistic virtual overlays to personalized dietary annotations.

In retail, AIs will use your purchasing history, current closet inventory, and possibly even mood indicators to display digitally rendered items most suitable for your wardrobe, tailored to your measurements.

In healthcare, smart AR glasses will provide physicians with immediately accessible and maximally relevant information (parsed from the entirety of a patient’s medical records and current research) to aid in accurate diagnoses and treatments, freeing doctors to engage in the more human-centric tasks of establishing trust, educating patients and demonstrating empathy.

Image Credit: PHD Ventures.
Convergence in Manufacturing
One of the nearest-term use cases of AR is manufacturing, as large producers begin dedicating capital to enterprise AR headsets. And over the next ten years, AR will converge with AI, sensors, and blockchain to multiply manufacturer productivity and employee experience.

(1) Convergence with AI
In initial application, digital guides superimposed on production tables will vastly improve employee accuracy and speed, while minimizing error rates.

Already, the International Air Transport Association (IATA) — whose airlines supply 82 percent of air travel — recently implemented industrial tech company Atheer’s AR headsets in cargo management. And with barely any delay, IATA reported a whopping 30 percent improvement in cargo handling speed and no less than a 90 percent reduction in errors.

With similar success rates, Boeing brought Skylight’s smart AR glasses to the runway, now used in the manufacturing of hundreds of airplanes. Sure enough—the aerospace giant has now seen a 25 percent drop in production time and near-zero error rates.

Beyond cargo management and air travel, however, smart AR headsets will also enable on-the-job training without reducing the productivity of other workers or sacrificing hardware. Jaguar Land Rover, for instance, implemented Bosch’s Re’flekt One AR solution to gear technicians with “x-ray” vision: allowing them to visualize the insides of Range Rover Sport vehicles without removing any dashboards.

And as enterprise capabilities continue to soar, AIs will soon become the go-to experts, offering support to manufacturers in need of assembly assistance. Instant guidance and real-time feedback will dramatically reduce production downtime, boost overall output, and even help customers struggling with DIY assembly at home.

Perhaps one of the most profitable business opportunities, AR guidance through centralized AI systems will also serve to mitigate supply chain inefficiencies at extraordinary scale. Coordinating moving parts, eliminating the need for manned scanners at each checkpoint, and directing traffic within warehouses, joint AI-AR systems will vastly improve workflow while overseeing quality assurance.

After its initial implementation of AR “vision picking” in 2015, leading courier company DHL recently announced it would continue to use Google’s newest smart lens in warehouses across the world. Motivated by the initial group’s reported 15 percent jump in productivity, DHL’s decision is part of the logistics giant’s $300 million investment in new technologies.

And as direct-to-consumer e-commerce fundamentally transforms the retail sector, supply chain optimization will only grow increasingly vital. AR could very well prove the definitive step for gaining a competitive edge in delivery speeds.

As explained by Vital Enterprises CEO Ash Eldritch, “All these technologies that are coming together around artificial intelligence are going to augment the capabilities of the worker and that’s very powerful. I call it Augmented Intelligence. The idea is that you can take someone of a certain skill level and by augmenting them with artificial intelligence via augmented reality and the Internet of Things, you can elevate the skill level of that worker.”

Already, large producers like Goodyear, thyssenkrupp, and Johnson Controls are using the Microsoft HoloLens 2—priced at $3,500 per headset—for manufacturing and design purposes.

Perhaps the most heartening outcome of the AI-AR convergence is that, rather than replacing humans in manufacturing, AR is an ideal interface for human collaboration with AI. And as AI merges with human capital, prepare to see exponential improvements in productivity, professional training, and product quality.

(2) Convergence with Sensors
On the hardware front, these AI-AR systems will require a mass proliferation of sensors to detect the external environment and apply computer vision in AI decision-making.

To measure depth, for instance, some scanning depth sensors project a structured pattern of infrared light dots onto a scene, detecting and analyzing reflected light to generate 3D maps of the environment. Stereoscopic imaging, using two lenses, has also been commonly used for depth measurements. But leading technology like Microsoft’s HoloLens 2 and Intel’s RealSense 400-series camera implement a new method called “phased time-of-flight” (ToF).

In ToF sensing, the HoloLens 2 uses numerous lasers, each with 100 milliwatts (mW) of power, in quick bursts. The distance between nearby objects and the headset wearer is then measured by the amount of light in the return beam that has shifted from the original signal. Finally, the phase difference reveals the location of each object within the field of view, which enables accurate hand-tracking and surface reconstruction.

With a far lower computing power requirement, the phased ToF sensor is also more durable than stereoscopic sensing, which relies on the precise alignment of two prisms. The phased ToF sensor’s silicon base also makes it easily mass-produced, rendering the HoloLens 2 a far better candidate for widespread consumer adoption.

To apply inertial measurement—typically used in airplanes and spacecraft—the HoloLens 2 additionally uses a built-in accelerometer, gyroscope, and magnetometer. Further equipped with four “environment understanding cameras” that track head movements, the headset also uses a 2.4MP HD photographic video camera and ambient light sensor that work in concert to enable advanced computer vision.

For natural viewing experiences, sensor-supplied gaze tracking increasingly creates depth in digital displays. Nvidia’s work on Foveated AR Display, for instance, brings the primary foveal area into focus, while peripheral regions fall into a softer background— mimicking natural visual perception and concentrating computing power on the area that needs it most.

Gaze tracking sensors are also slated to grant users control over their (now immersive) screens without any hand gestures. Conducting simple visual cues, even staring at an object for more than three seconds, will activate commands instantaneously.

And our manufacturing example above is not the only one. Stacked convergence of blockchain, sensors, AI and AR will disrupt almost every major industry.

Take healthcare, for example, wherein biometric sensors will soon customize users’ AR experiences. Already, MIT Media Lab’s Deep Reality group has created an underwater VR relaxation experience that responds to real-time brain activity detected by a modified version of the Muse EEG. The experience even adapts to users’ biometric data, from heart rate to electro dermal activity (inputted from an Empatica E4 wristband).

Now rapidly dematerializing, sensors will converge with AR to improve physical-digital surface integration, intuitive hand and eye controls, and an increasingly personalized augmented world. Keep an eye on companies like MicroVision, now making tremendous leaps in sensor technology.

While I’ll be doing a deep dive into sensor applications across each industry in our next blog, it’s critical to first discuss how we might power sensor- and AI-driven augmented worlds.

(3) Convergence with Blockchain
Because AR requires much more compute power than typical 2D experiences, centralized GPUs and cloud computing systems are hard at work to provide the necessary infrastructure. Nonetheless, the workload is taxing and blockchain may prove the best solution.

A major player in this pursuit, Otoy aims to create the largest distributed GPU network in the world, called the Render Network RNDR. Built specifically on the Ethereum blockchain for holographic media, and undergoing Beta testing, this network is set to revolutionize AR deployment accessibility.

Alphabet Chairman Eric Schmidt (an investor in Otoy’s network), has even said, “I predicted that 90% of computing would eventually reside in the web based cloud… Otoy has created a remarkable technology which moves that last 10%—high-end graphics processing—entirely to the cloud. This is a disruptive and important achievement. In my view, it marks the tipping point where the web replaces the PC as the dominant computing platform of the future.”

Leveraging the crowd, RNDR allows anyone with a GPU to contribute their power to the network for a commission of up to $300 a month in RNDR tokens. These can then be redeemed in cash or used to create users’ own AR content.

In a double win, Otoy’s blockchain network and similar iterations not only allow designers to profit when not using their GPUs, but also democratize the experience for newer artists in the field.

And beyond these networks’ power suppliers, distributing GPU processing power will allow more manufacturing companies to access AR design tools and customize learning experiences. By further dispersing content creation across a broad network of individuals, blockchain also has the valuable potential to boost AR hardware investment across a number of industry beneficiaries.

On the consumer side, startups like Scanetchain are also entering the blockchain-AR space for a different reason. Allowing users to scan items with their smartphone, Scanetchain’s app provides access to a trove of information, from manufacturer and price, to origin and shipping details.

Based on NEM (a peer-to-peer cryptocurrency that implements a blockchain consensus algorithm), the app aims to make information far more accessible and, in the process, create a social network of purchasing behavior. Users earn tokens by watching ads, and all transactions are hashed into blocks and securely recorded.

The writing is on the wall—our future of brick-and-mortar retail will largely lean on blockchain to create the necessary digital links.

Final Thoughts
Integrating AI into AR creates an “auto-magical” manufacturing pipeline that will fundamentally transform the industry, cutting down on marginal costs, reducing inefficiencies and waste, and maximizing employee productivity.

Bolstering the AI-AR convergence, sensor technology is already blurring the boundaries between our augmented and physical worlds, soon to be near-undetectable. While intuitive hand and eye motions dictate commands in a hands-free interface, biometric data is poised to customize each AR experience to be far more in touch with our mental and physical health.

And underpinning it all, distributed computing power with blockchain networks like RNDR will democratize AR, boosting global consumer adoption at plummeting price points.

As AR soars in importance—whether in retail, manufacturing, entertainment, or beyond—the stacked convergence discussed above merits significant investment over the next decade. The augmented world is only just getting started.

Join Me
(1) A360 Executive Mastermind: Want even more context about how converging exponential technologies will transform your business and industry? Consider joining Abundance 360, a highly selective community of 360 exponentially minded CEOs, who are on a 25-year journey with me—or as I call it, a “countdown to the Singularity.” If you’d like to learn more and consider joining our 2020 membership, apply here.

Share this with your friends, especially if they are interested in any of the areas outlined above.

(2) Abundance-Digital Online Community: I’ve also created a Digital/Online community of bold, abundance-minded entrepreneurs called Abundance-Digital. Abundance-Digital is Singularity University’s ‘onramp’ for exponential entrepreneurs — those who want to get involved and play at a higher level. Click here to learn more.

This article originally appeared on Diamandis.com

Image Credit: Funky Focus / Pixabay Continue reading

Posted in Human Robots

#435750 Video Friday: Amazon CEO Jeff Bezos ...

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):

RSS 2019 – June 22-26, 2019 – Freiburg, Germany
Hamlyn Symposium on Medical Robotics – June 23-26, 2019 – London, U.K.
ETH Robotics Summer School – June 27-1, 2019 – Zurich, Switzerland
MARSS 2019 – July 1-5, 2019 – Helsinki, Finland
ICRES 2019 – July 29-30, 2019 – London, U.K.
Let us know if you have suggestions for next week, and enjoy today’s videos.

Last week at the re:MARS conference, Amazon CEO and aspiring supervillain Jeff Bezos tried out this pair of dexterous robotic hands, which he described as “weirdly natural” to operate. The system combines Shadow Robot’s anthropomorphic robot hands with SynTouch’s biomimetic tactile sensors and HaptX’s haptic feedback gloves.

After playing with the robot, Bezos let out his trademark evil laugh.

[ Shadow Robot ]

The RoboMaster S1 is DJI’s advanced new educational robot that opens the door to limitless learning and entertainment. Develop programming skills, get familiar with AI technology, and enjoy thrilling FPV driving with games and competition. From young learners to tech enthusiasts, get ready to discover endless possibilities with the RoboMaster S1.

[ DJI ]

It’s very impressive to see DLR’s humanoid robot Toro dynamically balancing, even while being handed heavy objects, pushing things, and using multi-contact techniques to kick a fire extinguisher for some reason.

The paper is in RA-L, and you can find it at the link below.

[ RA-L ] via [ DLR ]

Thanks Maximo!

Is it just me, or does the Suzumori Endo Robotics Laboratory’s Super Dragon arm somehow just keep getting longer?

Suzumori Endo Lab, Tokyo Tech developed a 10 m-long articulated manipulator for investigation inside the primary containment vessel of the Fukushima Daiichi Nuclear Power Plants. We employed a coupled tendon-driven mechanism and a gravity compensation mechanism using synthetic fiber ropes to design a lightweight and slender articulated manipulator. This work was published in IEEE Robotics and Automation Letters and Transactions of the JSME.

[ Suzumori Endo Lab ]

From what I can make out thanks to Google Translate, this cute little robot duck (developed by Nissan) helps minimize weeds in rice fields by stirring up the water.

[ Nippon.com ]

Confidence in your robot is when you can just casually throw it off of a balcony 15 meters up.

[ SUTD ]

You had me at “we’re going to completely submerge this apple in chocolate syrup.”

[ Soft Robotics Inc ]

In the mid 2020s, the European Space Agency is planning on sending a robotic sample return mission to the Moon. It’s called Heracles, after the noted snake-strangler of Greek mythology.

[ ESA ]

Rethink Robotics is still around, they’re just much more German than before. And Sawyer is still hard at work stealing jobs from humans.

[ Rethink Robotics ]

The reason to watch this new video of the Ghost Robotics Vision 60 quadruped is for the 3 seconds worth of barrel roll about 40 seconds in.

[ Ghost Robotics ]

This is a relatively low-altitude drop for Squishy Robotics’ tensegrity scout, but it still cool to watch a robot that’s resilient enough to be able to fall and just not worry about it.

[ Squishy Robotics ]

We control here the Apptronik DRACO bipedal robot for unsupported dynamic locomotion. DRACO consists of a 10 DoF lower body with liquid cooled viscoelastic actuators to reduce weight, increase payload, and achieve fast dynamic walking. Control and walking algorithms are designed by UT HCRL Laboratory.

I think all robot videos should be required to start with two “oops” clips followed by a “for real now” clip.

[ Apptronik ]

SAKE’s EZGripper manages to pick up a wrench, and also pick up a raspberry without turning it into instajam.

[ SAKE Robotics ]

And now: the robotic long-tongued piggy, courtesy Sony Toio.

[ Toio ]

In this video the ornithopter developed inside the ERC Advanced Grant GRIFFIN project performs its first flight. This projects aims to develop a flapping wing system with manipulation and human interaction capabilities.

A flapping-wing system with manipulation and human interaction capabilities, you say? I would like to subscribe to your newsletter.

[ GRVC ]

KITECH’s robotic hands and arms can manipulate, among other things, five boxes of Elmos. I’m not sure about the conversion of Elmos to Snuffleupaguses, although it turns out that one Snuffleupagus is exactly 1,000 pounds.

[ Ji-Hun Bae ]

The Australian Centre for Field Robotics (ACFR) has been working on agricultural robots for almost a decade, and this video sums up a bunch of the stuff that they’ve been doing, even if it’s more amusing than practical at times.

[ ACFR ]

ROS 2 is great for multi-robot coordination, like when you need your bubble level to stay really, really level.

[ Acutronic Robotics ]

We don’t hear iRobot CEO Colin Angle give a lot of talks, so this recent one (from Amazon’s re:MARS conference) is definitely worth a listen, especially considering how much innovation we’ve seen from iRobot recently.

Colin Angle, founder and CEO of iRobot, has unveil a series of breakthrough innovations in home robots from iRobot. For the first time on stage, he will discuss and demonstrate what it takes to build a truly intelligent system of robots that work together to accomplish more within the home – and enable that home, and the devices within it, to work together as one.

[ iRobot ]

In the latest episode of Robots in Depth, Per speaks with Federico Pecora from the Center for Applied Autonomous Sensor Systems at Örebro University in Sweden.

Federico talks about working on AI and service robotics. In this area he has worked on planning, especially focusing on why a particular goal is the one that the robot should work on. To make robots as useful and user friendly as possible, he works on inferring the goal from the robot’s environment so that the user does not have to tell the robot everything.

Federico has also worked with AI robotics planning in industry to optimize results. Managing the relative importance of tasks is another challenging area there. In this context, he works on automating not only a single robot for its goal, but an entire fleet of robots for their collective goal. We get to hear about how these techniques are being used in warehouse operations, in mines and in agriculture.

[ Robots in Depth ] Continue reading

Posted in Human Robots

#435748 Video Friday: This Robot Is Like a ...

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!):

RSS 2019 – June 22-26, 2019 – Freiburg, Germany
Hamlyn Symposium on Medical Robotics – June 23-26, 2019 – London, U.K.
ETH Robotics Summer School – June 27-1, 2019 – Zurich, Switzerland
MARSS 2019 – July 1-5, 2019 – Helsinki, Finland
ICRES 2019 – July 29-30, 2019 – London, U.K.
DARPA SubT Tunnel Circuit – August 15-22, 2019 – Pittsburgh, Pa., USA
Let us know if you have suggestions for next week, and enjoy today’s videos.

It’s been a while since we last spoke to Joe Jones, the inventor of Roomba, about his solar-powered, weed-killing robot, called Tertill, which he was launching as a Kickstarter project. Tertill is now available for purchase (US $300) and is shipping right now.

[ Tertill ]

Usually, we don’t post videos that involve drone use that looks to be either illegal or unsafe. These flights over the protests in Hong Kong are almost certainly both. However, it’s also a unique perspective on the scale of these protests.

[ Team BlackSheep ]

ICYMI: iRobot announced this week that it has acquired Root Robotics.

[ iRobot ]

This Boston Dynamics parody video went viral this week.

The CGI is good but the gratuitous violence—even if it’s against a fake robot—is a bit too much?

This is still our favorite Boston Dynamics parody video:

[ Corridor ]

Biomedical Engineering Department Head Bin He and his team have developed the first-ever successful non-invasive mind-controlled robotic arm to continuously track a computer cursor.

[ CMU ]

Organic chemists, prepare to meet your replacement:

Automated chemical synthesis carries great promises of safety, efficiency and reproducibility for both research and industry laboratories. Current approaches are based on specifically-designed automation systems, which present two major drawbacks: (i) existing apparatus must be modified to be integrated into the automation systems; (ii) such systems are not flexible and would require substantial re-design to handle new reactions or procedures. In this paper, we propose a system based on a robot arm which, by mimicking the motions of human chemists, is able to perform complex chemical reactions without any modifications to the existing setup used by humans. The system is capable of precise liquid handling, mixing, filtering, and is flexible: new skills and procedures could be added with minimum effort. We show that the robot is able to perform a Michael reaction, reaching a yield of 34%, which is comparable to that obtained by a junior chemist (undergraduate student in Chemistry).

[ arXiv ] via [ NTU ]

So yeah, ICRA 2019 was huge and awesome. Here are some brief highlights.

[ Montreal Gazette ]

For about US $5, this drone will deliver raw meat and beer to you if you live on an uninhabited island in Tokyo Bay.

[ Nikkei ]

The Smart Microsystems Lab at Michigan State University has a new version of their Autonomous Surface Craft. It’s autonomous, open source, and awfully hard to sink.

[ SML ]

As drone shows go, this one is pretty good.

[ CCTV ]

Here’s a remote controlled robot shooting stuff with a very large gun.

[ HDT ]

Over a period of three quarters (September 2018 thru May 2019), we’ve had the opportunity to work with five graduating University of Denver students as they brought their idea for a Misty II arm extension to life.

[ Misty Robotics ]

If you wonder how it looks to inspect burners and superheaters of a boiler with an Elios 2, here you are! This inspection was performed by Svenska Elektrod in a peat-fired boiler for Vattenfall in Sweden. Enjoy!

[ Flyability ]

The newest Soft Robotics technology, mGrip mini fingers, made for tight spaces, small packaging, and delicate items, giving limitless opportunities for your applications.

[ Soft Robotics ]

What if legged robots were able to generate dynamic motions in real-time while interacting with a complex environment? Such technology would represent a significant step forward the deployment of legged systems in real world scenarios. This means being able to replace humans in the execution of dangerous tasks and to collaborate with them in industrial applications.

This workshop aims to bring together researchers from all the relevant communities in legged locomotion such as: numerical optimization, machine learning (ML), model predictive control (MPC) and computational geometry in order to chart the most promising methods to address the above-mentioned scientific challenges.

[ Num Opt Wkshp ]

Army researchers teamed with the U.S. Marine Corps to fly and test 3-D printed quadcopter prototypes a the Marine Corps Air Ground Combat Center in 29 Palms, California recently.

[ CCDC ARL ]

Lex Fridman’s Artificial Intelligence podcast featuring Rosalind Picard.

[ AI Podcast ]

In this week’s episode of Robots in Depth, per speaks with Christian Guttmann, executive director of the Nordic AI Artificial Intelligence Institute.

Christian Guttmann talks about AI and wanting to understand intelligence enough to recreate it. Christian has be focusing on AI in healthcare and has recently started to communicate the opportunities and challenges in artificial intelligence to the general public. This is something that the host Per Sjöborg is also very passionate about. We also get to hear about the Nordic AI institute and the work it does to inform all parts of society about AI.

[ Robots in Depth ] Continue reading

Posted in Human Robots

#435742 This ‘Useless’ Social Robot ...

The recent high profile failures of some home social robots (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.

One of those companies is Zoetic, founded in 2107 by Mita Yun and Jitu Das, both ex-Googlers. Their robot, Kiki, is more or less exactly what you’d expect from a social home robot: It’s cute, white, roundish, has big eyes, promises that it will be your “robot sidekick,” and is not cheap: It’s on Kicksterter for $800. Kiki is among what appears to be a sort of tentative second wave of social home robots, where designers have (presumably) had a chance to take everything that they learned from the social home robot pioneers and use it to make things better this time around.

Kiki’s Kickstarter video is, again, more or less exactly what you’d expect from a social home robot crowdfunding campaign:

We won’t get into all of the details on Kiki in this article (the Kickstarter page has tons of information), but a few distinguishing features:

Each Kiki will develop its own personality over time through its daily interactions with its owner, other people, and other Kikis.
Interacting with Kiki is more abstract than with most robots—it can understand some specific words and phrases, and will occasionally use a few specific words or two, but otherwise it’s mostly listening to your tone of voice and responding with sounds rather than speech.
Kiki doesn’t move on its own, but it can operate for up to two hours away from its charging dock.
Depending on how your treat Kiki, it can get depressed or neurotic. It also needs to be fed, which you can do by drawing different kinds of food in the app.
Everything Kiki does runs on-board the robot. It has Wi-Fi connectivity for updates, but doesn’t rely on the cloud for anything in real-time, meaning that your data stays on the robot and that the robot will continue to function even if its remote service shuts down.

It’s hard to say whether features like these are unique enough to help Kiki be successful where other social home robots haven’t been, so we spoke with Zoetic co-founder Mita Yun and asked her why she believes that Kiki is going to be the social home robot that makes it.

IEEE Spectrum: What’s your background?

Mita Yun: I was an only child growing up, and so I always wanted something like Doraemon or Totoro. Something that when you come home it’s there to greet you, not just because it’s programmed to do that but because it’s actually actively happy to see you, and only you. I was so interested in this that I went to study robotics at CMU and then after I graduated I joined Google and worked there for five years. I tended to go for the more risky and more fun projects, but they always got cancelled—the first project I joined was called Android at Home, and then I joined Google Glass, and then I joined a team called Robots for Kids. That project was building educational robots, and then I just realized that when we’re adding technology to something, to a product, we’re actually taking the life away somehow, and the kids were more connected with stuffed animals compared to the educational robots we were building. That project was also cancelled, and in 2017, I left with a coworker of mine (Jitu Das) to bring this dream into reality. And now we’re building Kiki.

“Jibo was Alexa plus cuteness equals $800, and I feel like that equation doesn’t work for most people, and that eventually killed the company. So, for Kiki, we are actually building something very different. We’re building something that’s completely useless”
—Mita Yun, Zoetic

You started working on Kiki in 2017, when things were already getting challenging for Jibo—why did you decide to start developing a social home robot at that point?

I thought Jibo was great. It had a special magical way of moving, and it was such a new idea that you could have this robot with embodiment and it can actually be your assistant. The problem with Jibo, in my opinion, was that it took too long to fulfill the orders. It took them three to four years to actually manufacture, because it was a very complex piece of hardware, and then during that period of time Alexa and Google Home came out, and they started selling these voice systems for $30 and then you have Jibo for $800. Jibo was Alexa plus cuteness equals $800, and I feel like that equation doesn’t work for most people, and that eventually killed the company. So, for Kiki, we are actually building something very different. We’re building something that’s completely useless.

Can you elaborate on “completely useless?”

I feel like people are initially connected with robots because they remind them of a character. And it’s the closest we can get to a character other than an organic character like an animal. So we’re connected to a character like when we have a robot in a mall that’s roaming around, even if it looks really ugly, like if it doesn’t have eyes, people still take selfies with it. Why? Because they think it’s a character. And humans are just hardwired to love characters and love stories. With Kiki, we just wanted to build a character that’s alive, we don’t want to have a character do anything super useful.

I understand why other robotics companies are adding Alexa integration to their robots, and I think that’s great. But the dream I had, and the understanding I have about robotics technology, is that for a consumer robot especially, it is very very difficult for the robot to justify its price through usefulness. And then there’s also research showing that the more useless something is, the easier it is to have an emotional connection, so that’s why we want to keep Kiki very useless.

What kind of character are you creating with Kiki?

The whole design principle around Kiki is we want to make it a very vulnerable character. In terms of its status at home, it’s not going to be higher or equal status as the owner, but slightly lower status than the human, and it’s vulnerable and needs you to take care of it in order to grow up into a good personality robot.

We don’t let Kiki speak full English sentences, because whenever it does that, people are going to think it’s at least as intelligent as a baby, which is impossible for robots at this point. And we also don’t let it move around, because when you have it move around, people are going to think “I’m going to call Kiki’s name, and then Kiki is will come to me.” But that is actually very difficult to build. And then also we don’t have any voice integration so it doesn’t tell you about the stock market price and so on.

Photo: Zoetic

Kiki is designed to be “vulnerable,” and it needs you to take care of it so it can “grow up into a good personality robot,” according to its creators.

That sounds similar to what Mayfield did with Kuri, emphasizing an emotional connection rather than specific functionality.

It is very similar, but one of the key differences from Kuri, I think, is that Kuri started with a Kobuki base, and then it’s wrapped into a cute shell, and they added sounds. So Kuri started with utility in mind—navigation is an important part of Kuri, so they started with that challenge. For Kiki, we started with the eyes. The entire thing started with the character itself.

How will you be able to convince your customers to spend $800 on a robot that you’ve described as “useless” in some ways?

Because it’s useless, it’s actually easier to convince people, because it provides you with an emotional connection. I think Kiki is not a utility-driven product, so the adoption cycle is different. For a functional product, it’s very easy to pick up, because you can justify it by saying “I’m going to pay this much and then my life can become this much more efficient.” But it’s also very easy to be replaced and forgotten. For an emotional-driven product, it’s slower to pick up, but once people actually pick it up, they’re going to be hooked—they get be connected with it, and they’re willing to invest more into taking care of the robot so it will grow up to be smarter.

Maintaining value over time has been another challenge for social home robots. How will you make sure that people don’t get bored with Kiki after a few weeks?

Of course Kiki has limits in what it can do. We can combine the eyes, the facial expression, the motors, and lights and sounds, but is it going to be constantly entertaining? So we think of this as, imagine if a human is actually puppeteering Kiki—can Kiki stay interesting if a human is puppeteering it and interacting with the owner? So I think what makes a robot interesting is not just in the physical expressions, but the part in between that and the robot conveying its intentions and emotions.

For example, if you come into the room and then Kiki decides it will turn the other direction, ignore you, and then you feel like, huh, why did the robot do that to me? Did I do something wrong? And then maybe you will come up to it and you will try to figure out why it did that. So, even though Kiki can only express in four different dimensions, it can still make things very interesting, and then when its strategies change, it makes it feel like a new experience.

There’s also an explore and exploit process going on. Kiki wants to make you smile, and it will try different things. It could try to chase its tail, and if you smile, Kiki learns that this works and will exploit it. But maybe after doing it three times, you no longer find it funny, because you’re bored of it, and then Kiki will observe your reactions and be motivated to explore a new strategy.

Photo: Zoetic

Kiki’s creators are hoping that, with an emotionally engaging robot, it will be easier for people to get attached to it and willing to spend time taking care of it.

A particular risk with crowdfunding a robot like this is setting expectations unreasonably high. The emphasis on personality and emotional engagement with Kiki seems like it may be very difficult for the robot to live up to in practice.

I think we invested more than most robotics companies into really building out Kiki’s personality, because that is the single most important thing to us. For Jibo a lot of the focus was in the assistant, and for Kuri, it’s more in the movement. For Kiki, it’s very much in the personality.

I feel like when most people talk about personality, they’re mainly talking about expression. With Kiki, it’s not just in the expression itself, not just in the voice or the eyes or the output layer, it’s in the layer in between—when Kiki receives input, how will it make decisions about what to do? We actually don’t think the personality of Kiki is categorizable, which is why I feel like Kiki has a deeper implementation of how personalities should work. And you’re right, Kiki doesn’t really understand why you’re feeling a certain way, it just reads your facial expressions. It’s maybe not your best friend, but maybe closer to your little guinea pig robot.

Photo: Zoetic

The team behind Kiki paid particular attention to its eyes, and designed the robot to always face the person that it is interacting with.

Is that where you’d put Kiki on the scale of human to pet?

Kiki is definitely not human, we want to keep it very far away from human. And it’s also not a dog or cat. When we were designing Kiki, we took inspiration from mammals because humans are deeply connected to mammals since we’re mammals ourselves. And specifically we’re connected to predator animals. With prey animals, their eyes are usually on the sides of their heads, because they need to see different angles. A predator animal needs to hunt, they need to focus. Cats and dogs are predator animals. So with Kiki, that’s why we made sure the eyes are on one side of the face and the head can actuate independently from the body and the body can turn so it’s always facing the person that it’s paying attention to.

I feel like Kiki is probably does more than a plant. It does more than a fish, because a fish doesn’t look you in the eyes. It’s not as smart as a cat or a dog, so I would just put it in this guinea pig kind of category.

What have you found so far when running user studies with Kiki?

When we were first designing Kiki we went through a whole series of prototypes. One of the earlier prototypes of Kiki looked like a CRT, like a very old monitor, and when we were testing that with people they didn’t even want to touch it. Kiki’s design inspiration actually came from an airplane, with a very angular, futuristic look, but based on user feedback we made it more round and more friendly to the touch. The lights were another feature request from the users, which adds another layer of expressivity to Kiki, and they wanted to see multiple Kikis working together with different personalities. Users also wanted different looks for Kiki, to make it look like a deer or a unicorn, for example, and we actually did take that into consideration because it doesn’t look like any particular mammal. In the future, you’ll be able to have different ears to make it look like completely different animals.

There has been a lot of user feedback that we didn’t implement—I believe we should observe the users reactions and feedback but not listen to their advice. The users shouldn’t be our product designers, because if you test Kiki with 10 users, eight of them will tell you they want Alexa in it. But we’re never going to add Alexa integration to Kiki because that’s not what it’s meant to do.

While it’s far too early to tell whether Kiki will be a long-term success, the Kickstarter campaign is currently over 95 percent funded with 8 days to go, and 34 robots are still available for a May 2020 delivery.

[ Kickstarter ] Continue reading

Posted in Human Robots

#435738 Boing Goes the Trampoline Robot

There are a handful of quadrupedal robots out there that are highly dynamic, with the ability to run and jump, but those robots tend to be rather expensive and complicated, requiring powerful actuators and legs with elasticity. Boxing Wang, a Ph.D. student in the College of Control Science and Engineering at Zhejiang University in China, contacted us to share a project he’s been working to investigate quadruped jumping with simple, affordable hardware.

“The motivation for this project is quite simple,” Boxing says. “I wanted to study quadrupedal jumping control, but I didn’t have custom-made powerful actuators, and I didn’t want to have to design elastic legs. So I decided to use a trampoline to make a normal servo-driven quadruped robot to jump.”

Boxing and his colleagues had wanted to study quadrupedal running and jumping, so they built this robot with the most powerful servos they had access to: Kondo KRS6003RHV actuators, which have a maximum torque of 6 Nm. After some simple testing, it became clear that the servos were simply not fast or powerful enough to get the robot to jump, and that an elastic element was necessary to store energy to help the robot get off the ground.

“Normally, people would choose elastic legs,” says Boxing. “But nobody in my lab knew for sure how to design them. If we tried making elastic legs and we failed to make the robot jump, we couldn’t be sure whether the problem was the legs or the control algorithms. For hardware, we decided that it’s better to start with something reliable, something that definitely won’t be the source of the problem.”

As it turns out, all you need is a trampoline, an inertial measurement unit (IMU), and little tactile switches on the end of each foot to detect touch-down and lift-off events, and you can do some useful jumping research without a jumping robot. And the trampoline has other benefits as well—because it’s stiffer at the edges than at the center, for example, the robot will tend to center itself on the trampoline, and you get some warning before things go wrong.

“I can’t say that it’s a breakthrough to make a quadruped robot jump on a trampoline,” Boxing tells us. “But I believe this is useful for prototype testing, especially for people who are interested in quadrupedal jumping control but without a suitable robot at hand.”

To learn more about the project, we emailed him some additional questions.

IEEE Spectrum: Where did this idea come from?

Boxing Wang: The idea of the trampoline came while we were drinking milk tea. I don’t know why it came up, maybe someone saw a trampoline in a gym recently. And I don’t remember who proposed it exactly. It was just like someone said it unintentionally. But I realized that a trampoline would be a perfect choice. It’s reliable, easy to buy, and should have a similar dynamic model with the one of jumping with springy legs (we have briefly analyzed this in a paper). So I decided to try the trampoline.

How much do you think you can learn using a quadruped on a trampoline, instead of using a jumping quadruped?

Generally speaking, no contact surfaces are strictly rigid. They all have elasticity. So there are no essential differences between jumping on a trampoline and jumping on a rigid surface. However, using a quadruped on a trampoline can give you more information on how to make use of elasticity to make jumping easier and more efficient. You can use quadruped robots with springy legs to address the same problem, but that usually requires much more time on hardware design.

We prefer to treat the trampoline experiment as a kind of early test for further real jumping quadruped design. Unless you’re interested in designing an acrobatic robot on a trampoline, a real jumping quadruped is probably a more useful application, and that is our ultimate goal. The point of the trampoline tests is to develop the control algorithms first, and to examine the stability of the general hardware structure. Due to the similarity between jumping on a trampoline with rigid legs and jumping on hard surfaces with springy legs, the control algorithms you develop could be transferred to hard-surface jumping robots.

“Unless you’re interested in designing an acrobatic robot on a trampoline, a real jumping quadruped is probably a more useful application, and that is our ultimate goal. The point of the trampoline tests is to develop the control algorithms first, and to examine the stability of the general hardware structure”

Do you think that this idea can be beneficial for other kinds of robotics research?

Yes. For jumping quadrupeds with springy legs, the control algorithms could be first designed through trampoline tests using simple rigid legs. And the hardware design for elastic legs could be accelerated with the help of the control algorithms you design. In addition, we believe our work could be a good example of using a position-control robot to realize dynamic motions such as jumping, or even running.

Unlike other dynamic robots, every active joint in our robot is controlled through commercial position-control servos and not custom torque control motors. Most people don’t think that a position-control robot could perform highly dynamic motions such as jumping, because position-control motors usually mean high a gear ratio and slow response. However, our work indicates that, with the help of elasticity, stable jumping could be realized through position-control servos. So for those who already have a position-control robot at hand, they could explore the potential of their robot through trampoline tests.

Why is teaching a robot to jump important?

There are many scenarios where a jumping robot is needed. For example, a real jumping quadruped could be used to design a running quadruped. Both experience moments when all four legs are in the air, and it is easier to start from jumping and then move to running. Specifically, hopping or pronking can easily transform to bounding if the pitch angle is not strictly controlled. A bounding quadruped is similar to a running rabbit, so for now it can already be called a running quadruped.

To the best of our knowledge, a practical use of jumping quadrupeds could be planet exploration, just like what SpaceBok was designed for. In a low-gravity environment, jumping is more efficient than walking, and it’s easier to jump over obstacles. But if I had a jumping quadruped on Earth, I would teach it to catch a ball that I throw at it by jumping. It would be fantastic!

That would be fantastic.

Since the whole point of the trampoline was to get jumping software up and running with a minimum of hardware, the next step is to add some springy legs to the robot so that the control system the researchers developed can be tested on hard surfaces. They have a journal paper currently under revision, and Boxing Wang is joined as first author by his adviser Chunlin Zhou, undergrads Ziheng Duan and Qichao Zhu, and researchers Jun Wu and Rong Xiong. Continue reading

Posted in Human Robots