Tag Archives: reality

#435601 New Double 3 Robot Makes Telepresence ...

Today, Double Robotics is announcing Double 3, the latest major upgrade to its line of consumer(ish) telepresence robots. We had a (mostly) fantastic time testing out Double 2 back in 2016. One of the things that we found out back then was that it takes a lot of practice to remotely drive the robot around. Double 3 solves this problem by leveraging the substantial advances in 3D sensing and computing that have taken place over the past few years, giving their new robot a level of intelligence that promises to make telepresence more accessible for everyone.

Double 2’s iPad has been replaced by “a fully integrated solution”—which is a fancy way of saying a dedicated 9.7-inch touchscreen and a whole bunch of other stuff. That other stuff includes an NVIDIA Jetson TX2 AI computing module, a beamforming six-microphone array, an 8-watt speaker, a pair of 13-megapixel cameras (wide angle and zoom) on a tilting mount, five ultrasonic rangefinders, and most excitingly, a pair of Intel RealSense D430 depth sensors.

It’s those new depth sensors that really make Double 3 special. The D430 modules each uses a pair of stereo cameras with a pattern projector to generate 1280 x 720 depth data with a range of between 0.2 and 10 meters away. The Double 3 robot uses all of this high quality depth data to locate obstacles, but at this point, it still doesn’t drive completely autonomously. Instead, it presents the remote operator with a slick, augmented reality view of drivable areas in the form of a grid of dots. You just click where you want the robot to go, and it will skillfully take itself there while avoiding obstacles (including dynamic obstacles) and related mishaps along the way.

This effectively offloads the most stressful part of telepresence—not running into stuff—from the remote user to the robot itself, which is the way it should be. That makes it that much easier to encourage people to utilize telepresence for the first time. The way the system is implemented through augmented reality is particularly impressive, I think. It looks like it’s intuitive enough for an inexperienced user without being restrictive, and is a clever way of mitigating even significant amounts of lag.

Otherwise, Double 3’s mobility system is exactly the same as the one featured on Double 2. In fact, that you can stick a Double 3 head on a Double 2 body and it instantly becomes a Double 3. Double Robotics is thoughtfully offering this to current Double 2 owners as a significantly more affordable upgrade option than buying a whole new robot.

For more details on all of Double 3's new features, we spoke with the co-founders of Double Robotics, Marc DeVidts and David Cann.

IEEE Spectrum: Why use this augmented reality system instead of just letting the user click on a regular camera image? Why make things more visually complicated, especially for new users?

Marc DeVidts and David Cann: One of the things that we realized about nine months ago when we got this whole thing working was that without the mixed reality for driving, it was really too magical of an experience for the customer. Even us—we had a hard time understanding whether the robot could really see obstacles and understand where the floor is and that kind of thing. So, we said “What would be the best way of communicating this information to the user?” And the right way to do it ended up drawing the graphics directly onto the scene. It’s really awesome—we have a full, real time 3D scene with the depth information drawn on top of it. We’re starting with some relatively simple graphics, and we’ll be adding more graphics in the future to help the user understand what the robot is seeing.

How robust is the vision system when it comes to obstacle detection and avoidance? Does it work with featureless surfaces, IR absorbent surfaces, in low light, in direct sunlight, etc?

We’ve looked at all of those cases, and one of the reasons that we’re going with the RealSense is the projector that helps us to see blank walls. We also found that having two sensors—one facing the floor and one facing forward—gives us a great coverage area. Having ultrasonic sensors in there as well helps us to detect anything that we can't see with the cameras. They're sort of a last safety measure, especially useful for detecting glass.

It seems like there’s a lot more that you could do with this sensing and mapping capability. What else are you working on?

We're starting with this semi-autonomous driving variant, and we're doing a private beta of full mapping. So, we’re going to do full SLAM of your environment that will be mapped by multiple robots at the same time while you're driving, and then you'll be able to zoom out to a map and click anywhere and it will drive there. That's where we're going with it, but we want to take baby steps to get there. It's the obvious next step, I think, and there are a lot more possibilities there.

Do you expect developers to be excited for this new mapping capability?

We're using a very powerful computer in the robot, a NVIDIA Jetson TX2 running Ubuntu. There's room to grow. It’s actually really exciting to be able to see, in real time, the 3D pose of the robot along with all of the depth data that gets transformed in real time into one view that gives you a full map. Having all of that data and just putting those pieces together and getting everything to work has been a huge feat in of itself.

We have an extensive API for developers to do custom implementations, either for telepresence or other kinds of robotics research. Our system isn't running ROS, but we're going to be adding ROS adapters for all of our hardware components.

Telepresence robots depend heavily on wireless connectivity, which is usually not something that telepresence robotics companies like Double have direct control over. Have you found that connectivity has been getting significantly better since you first introduced Double?

When we started in 2013, we had a lot of customers that didn’t have WiFi in their hallways, just in the conference rooms. We very rarely hear about customers having WiFi connectivity issues these days. The bigger issue we see is when people are calling into the robot from home, where they don't have proper traffic management on their home network. The robot doesn't need a ton of bandwidth, but it does need consistent, low latency bandwidth. And so, if someone else in the house is watching Netflix or something like that, it’s going to saturate your connection. But for the most part, it’s gotten a lot better over the last few years, and it’s no longer a big problem for us.

Do you think 5G will make a significant difference to telepresence robots?

We’ll see. We like the low latency possibilities and the better bandwidth, but it's all going to be a matter of what kind of reception you get. LTE can be great, if you have good reception; it’s all about where the tower is. I’m pretty sure that WiFi is going to be the primary thing for at least the next few years.

DeVidts also mentioned that an unfortunate side effect of the new depth sensors is that hanging a t-shirt on your Double to give it some personality will likely render it partially blind, so that's just something to keep in mind. To make up for this, you can switch around the colorful trim surrounding the screen, which is nowhere near as fun.

When the Double 3 is ready for shipping in late September, US $2,000 will get you the new head with all the sensors and stuff, which seamlessly integrates with your Double 2 base. Buying Double 3 straight up (with the included charging dock) will run you $4,ooo. This is by no means an inexpensive robot, and my impression is that it’s not really designed for individual consumers. But for commercial, corporate, healthcare, or education applications, $4k for a robot as capable as the Double 3 is really quite a good deal—especially considering the kinds of use cases for which it’s ideal.

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#435589 Construction Robots Learn to Excavate by ...

Pavel Savkin remembers the first time he watched a robot imitate his movements. Minutes earlier, the engineer had finished “showing” the robotic excavator its new goal by directing its movements manually. Now, running on software Savkin helped design, the robot was reproducing his movements, gesture for gesture. “It was like there was something alive in there—but I knew it was me,” he said.

Savkin is the CTO of SE4, a robotics software project that styles itself the “driver” of a fleet of robots that will eventually build human colonies in space. For now, SE4 is focused on creating software that can help developers communicate with robots, rather than on building hardware of its own.
The Tokyo-based startup showed off an industrial arm from Universal Robots that was running SE4’s proprietary software at SIGGRAPH in July. SE4’s demonstration at the Los Angeles innovation conference drew the company’s largest audience yet. The robot, nicknamed Squeezie, stacked real blocks as directed by SE4 research engineer Nathan Quinn, who wore a VR headset and used handheld controls to “show” Squeezie what to do.

As Quinn manipulated blocks in a virtual 3D space, the software learned a set of ordered instructions to be carried out in the real world. That order is essential for remote operations, says Quinn. To build remotely, developers need a way to communicate instructions to robotic builders on location. In the age of digital construction and industrial robotics, giving a computer a blueprint for what to build is a well-explored art. But operating on a distant object—especially under conditions that humans haven’t experienced themselves—presents challenges that only real-time communication with operators can solve.

The problem is that, in an unpredictable setting, even simple tasks require not only instruction from an operator, but constant feedback from the changing environment. Five years ago, the Swedish fiber network provider umea.net (part of the private Umeå Energy utility) took advantage of the virtual reality boom to promote its high-speed connections with the help of a viral video titled “Living with Lag: An Oculus Rift Experiment.” The video is still circulated in VR and gaming circles.

In the experiment, volunteers donned headgear that replaced their real-time biological senses of sight and sound with camera and audio feeds of their surroundings—both set at a 3-second delay. Thus equipped, volunteers attempt to complete everyday tasks like playing ping-pong, dancing, cooking, and walking on a beach, with decidedly slapstick results.

At outer-orbit intervals, including SE4’s dream of construction projects on Mars, the limiting factor in communication speed is not an artificial delay, but the laws of physics. The shifting relative positions of Earth and Mars mean that communications between the planets—even at the speed of light—can take anywhere from 3 to 22 minutes.

A long-distance relationship

Imagine trying to manage a construction project from across an ocean without the benefit of intelligent workers: sending a ship to an unknown world with a construction crew and blueprints for a log cabin, and four months later receiving a letter back asking how to cut down a tree. The parallel problem in long-distance construction with robots, according to SE4 CEO Lochlainn Wilson, is that automation relies on predictability. “Every robot in an industrial setting today is expecting a controlled environment.”
Platforms for applying AR and VR systems to teach tasks to artificial intelligences, as SE4 does, are already proliferating in manufacturing, healthcare, and defense. But all of the related communications systems are bound by physics and, specifically, the speed of light.
The same fundamental limitation applies in space. “Our communications are light-based, whether they’re radio or optical,” says Laura Seward Forczyk, a planetary scientist and consultant for space startups. “If you’re going to Mars and you want to communicate with your robot or spacecraft there, you need to have it act semi- or mostly-independently so that it can operate without commands from Earth.”

Semantic control
That’s exactly what SE4 aims to do. By teaching robots to group micro-movements into logical units—like all the steps to building a tower of blocks—the Tokyo-based startup lets robots make simple relational judgments that would allow them to receive a full set of instruction modules at once and carry them out in order. This sidesteps the latency issue in real-time bilateral communications that could hamstring a project or at least make progress excruciatingly slow.
The key to the platform, says Wilson, is the team’s proprietary operating software, “Semantic Control.” Just as in linguistics and philosophy, “semantics” refers to meaning itself, and meaning is the key to a robot’s ability to make even the smallest decisions on its own. “A robot can scan its environment and give [raw data] to us, but it can’t necessarily identify the objects around it and what they mean,” says Wilson.

That’s where human intelligence comes in. As part of the demonstration phase, the human operator of an SE4-controlled machine “annotates” each object in the robot’s vicinity with meaning. By labeling objects in the VR space with useful information—like which objects are building material and which are rocks—the operator helps the robot make sense of its real 3D environment before the building begins.

Giving robots the tools to deal with a changing environment is an important step toward allowing the AI to be truly independent, but it’s only an initial step. “We’re not letting it do absolutely everything,” said Quinn. “Our robot is good at moving an object from point A to point B, but it doesn’t know the overall plan.” Wilson adds that delegating environmental awareness and raw mechanical power to separate agents is the optimal relationship for a mixed human-robot construction team; it “lets humans do what they’re good at, while robots do what they do best.”

This story was updated on 4 September 2019. Continue reading

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#435520 These Are the Meta-Trends Shaping the ...

Life is pretty different now than it was 20 years ago, or even 10 years ago. It’s sort of exciting, and sort of scary. And hold onto your hat, because it’s going to keep changing—even faster than it already has been.

The good news is, maybe there won’t be too many big surprises, because the future will be shaped by trends that have already been set in motion. According to Singularity University co-founder and XPRIZE founder Peter Diamandis, a lot of these trends are unstoppable—but they’re also pretty predictable.

At SU’s Global Summit, taking place this week in San Francisco, Diamandis outlined some of the meta-trends he believes are key to how we’ll live our lives and do business in the (not too distant) future.

Increasing Global Abundance
Resources are becoming more abundant all over the world, and fewer people are seeing their lives limited by scarcity. “It’s hard for us to realize this as we see crisis news, but what people have access to is more abundant than ever before,” Diamandis said. Products and services are becoming cheaper and thus available to more people, and having more resources then enables people to create more, thus producing even more resources—and so on.

Need evidence? The proportion of the world’s population living in extreme poverty is currently lower than it’s ever been. The average human life expectancy is longer than it’s ever been. The costs of day-to-day needs like food, energy, transportation, and communications are on a downward trend.

Take energy. In most of the world, though its costs are decreasing, it’s still a fairly precious commodity; we turn off our lights and our air conditioners when we don’t need them (ideally, both to save money and to avoid wastefulness). But the cost of solar energy has plummeted, and the storage capacity of batteries is improving, and solar technology is steadily getting more efficient. Bids for new solar power plants in the past few years have broken each other’s records for lowest cost per kilowatt hour.

“We’re not far from a penny per kilowatt hour for energy from the sun,” Diamandis said. “And if you’ve got energy, you’ve got water.” Desalination, for one, will be much more widely feasible once the cost of the energy needed for it drops.

Knowledge is perhaps the most crucial resource that’s going from scarce to abundant. All the world’s knowledge is now at the fingertips of anyone who has a mobile phone and an internet connection—and the number of people connected is only going to grow. “Everyone is being connected at gigabit connection speeds, and this will be transformative,” Diamandis said. “We’re heading towards a world where anyone can know anything at any time.”

Increasing Capital Abundance
It’s not just goods, services, and knowledge that are becoming more plentiful. Money is, too—particularly money for business. “There’s more and more capital available to invest in companies,” Diamandis said. As a result, more people are getting the chance to bring their world-changing ideas to life.

Venture capital investments reached a new record of $130 billion in 2018, up from $84 billion in 2017—and that’s just in the US. Globally, VC funding grew 21 percent from 2017 to a total of $207 billion in 2018.

Through crowdfunding, any person in any part of the world can present their idea and ask for funding. That funding can come in the form of a loan, an equity investment, a reward, or an advanced purchase of the proposed product or service. “Crowdfunding means it doesn’t matter where you live, if you have a great idea you can get it funded by people from all over the world,” Diamandis said.

All this is making a difference; the number of unicorns—privately-held startups valued at over $1 billion—currently stands at an astounding 360.

One of the reasons why the world is getting better, Diamandis believes, is because entrepreneurs are trying more crazy ideas—not ideas that are reasonable or predictable or linear, but ideas that seem absurd at first, then eventually end up changing the world.

Everyone and Everything, Connected
As already noted, knowledge is becoming abundant thanks to the proliferation of mobile phones and wireless internet; everyone’s getting connected. In the next decade or sooner, connectivity will reach every person in the world. 5G is being tested and offered for the first time this year, and companies like Google, SpaceX, OneWeb, and Amazon are racing to develop global satellite internet constellations, whether by launching 12,000 satellites, as SpaceX’s Starlink is doing, or by floating giant balloons into the stratosphere like Google’s Project Loon.

“We’re about to reach a period of time in the next four to six years where we’re going from half the world’s people being connected to the whole world being connected,” Diamandis said. “What happens when 4.2 billion new minds come online? They’re all going to want to create, discover, consume, and invent.”

And it doesn’t stop at connecting people. Things are becoming more connected too. “By 2020 there will be over 20 billion connected devices and more than one trillion sensors,” Diamandis said. By 2030, those projections go up to 500 billion and 100 trillion. Think about it: there’s home devices like refrigerators, TVs, dishwashers, digital assistants, and even toasters. There’s city infrastructure, from stoplights to cameras to public transportation like buses or bike sharing. It’s all getting smart and connected.

Soon we’ll be adding autonomous cars to the mix, and an unimaginable glut of data to go with them. Every turn, every stop, every acceleration will be a data point. Some cars already collect over 25 gigabytes of data per hour, Diamandis said, and car data is projected to generate $750 billion of revenue by 2030.

“You’re going to start asking questions that were never askable before, because the data is now there to be mined,” he said.

Increasing Human Intelligence
Indeed, we’ll have data on everything we could possibly want data on. We’ll also soon have what Diamandis calls just-in-time education, where 5G combined with artificial intelligence and augmented reality will allow you to learn something in the moment you need it. “It’s not going and studying, it’s where your AR glasses show you how to do an emergency surgery, or fix something, or program something,” he said.

We’re also at the beginning of massive investments in research working towards connecting our brains to the cloud. “Right now, everything we think, feel, hear, or learn is confined in our synaptic connections,” Diamandis said. What will it look like when that’s no longer the case? Companies like Kernel, Neuralink, Open Water, Facebook, Google, and IBM are all investing billions of dollars into brain-machine interface research.

Increasing Human Longevity
One of the most important problems we’ll use our newfound intelligence to solve is that of our own health and mortality, making 100 years old the new 60—then eventually, 120 or 150.

“Our bodies were never evolved to live past age 30,” Diamandis said. “You’d go into puberty at age 13 and have a baby, and by the time you were 26 your baby was having a baby.”

Seeing how drastically our lifespans have changed over time makes you wonder what aging even is; is it natural, or is it a disease? Many companies are treating it as one, and using technologies like senolytics, CRISPR, and stem cell therapy to try to cure it. Scaffolds of human organs can now be 3D printed then populated with the recipient’s own stem cells so that their bodies won’t reject the transplant. Companies are testing small-molecule pharmaceuticals that can stop various forms of cancer.

“We don’t truly know what’s going on inside our bodies—but we can,” Diamandis said. “We’re going to be able to track our bodies and find disease at stage zero.”

Chins Up
The world is far from perfect—that’s not hard to see. What’s less obvious but just as true is that we’re living in an amazing time. More people are coming together, and they have more access to information, and that information moves faster, than ever before.

“I don’t think any of us understand how fast the world is changing,” Diamandis said. “Most people are fearful about the future. But we should be excited about the tools we now have to solve the world’s problems.”

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#435505 This Week’s Awesome Stories From ...

AUGMENTED REALITY
This Is the Computer You’ll Wear on Your Face in 10 Years
Mark Sullivan | Fast Company
“[Snap’s new Spectacles 3] foreshadow a device that many of us may wear as our primary personal computing device in about 10 years. Based on what I’ve learned by talking AR with technologists in companies big and small, here is what such a device might look like and do.”

ROBOTICS
These Robo-Shorts Are the Precursor to a True Robotic Exoskeleton
Devin Coldewey | TechCrunch
“The whole idea, then, is to leave behind the idea of an exosuit as a big mechanical thing for heavy industry or work, and bring in the idea that one could help an elderly person stand up from a chair, or someone recovering from an accident walk farther without fatigue.”

ENVIRONMENT
Artificial Tree Promises to Suck Up as Much Air Pollution as a Small Forest
Luke Dormehl | Digital Trends
“The company has developed an artificial tree that it claims is capable of sucking up the equivalent amount of air pollution as 368 living trees. That’s not only a saving on growing time, but also on the space needed to accommodate them.”

FUTURE
The Anthropocene Is a Joke
Peter Brannen | The Atlantic
“Unless we fast learn how to endure on this planet, and on a scale far beyond anything we’ve yet proved ourselves capable of, the detritus of civilization will be quickly devoured by the maw of deep time.”

ARTIFICIAL INTELLIGENCE
DeepMind’s Losses and the Future of Artificial Intelligence
Gary Marcus | Wired
“Still, the rising magnitude of DeepMind’s losses is worth considering: $154 million in 2016, $341 million in 2017, $572 million in 2018. In my view, there are three central questions: Is DeepMind on the right track scientifically? Are investments of this magnitude sound from Alphabet’s perspective? And how will the losses affect AI in general?”

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#435308 Brain-Machine Interfaces Are Getting ...

Elon Musk grabbed a lot of attention with his July 16 announcement that his company Neuralink plans to implant electrodes into the brains of people with paralysis by next year. Their first goal is to create assistive technology to help people who can’t move or are unable to communicate.

If you haven’t been paying attention, brain-machine interfaces (BMIs) that allow people to control robotic arms with their thoughts might sound like science fiction. But science and engineering efforts have already turned it into reality.

In a few research labs around the world, scientists and physicians have been implanting devices into the brains of people who have lost the ability to control their arms or hands for over a decade. In our own research group at the University of Pittsburgh, we’ve enabled people with paralyzed arms and hands to control robotic arms that allow them to grasp and move objects with relative ease. They can even experience touch-like sensations from their own hand when the robot grasps objects.

At its core, a BMI is pretty straightforward. In your brain, microscopic cells called neurons are sending signals back and forth to each other all the time. Everything you think, do and feel as you interact with the world around you is the result of the activity of these 80 billion or so neurons.

If you implant a tiny wire very close to one of these neurons, you can record the electrical activity it generates and send it to a computer. Record enough of these signals from the right area of the brain and it becomes possible to control computers, robots, or anything else you might want, simply by thinking about moving. But doing this comes with tremendous technical challenges, especially if you want to record from hundreds or thousands of neurons.

What Neuralink Is Bringing to the Table
Elon Musk founded Neuralink in 2017, aiming to address these challenges and raise the bar for implanted neural interfaces.

Perhaps the most impressive aspect of Neuralink’s system is the breadth and depth of their approach. Building a BMI is inherently interdisciplinary, requiring expertise in electrode design and microfabrication, implantable materials, surgical methods, electronics, packaging, neuroscience, algorithms, medicine, regulatory issues, and more. Neuralink has created a team that spans most, if not all, of these areas.

With all of this expertise, Neuralink is undoubtedly moving the field forward, and improving their technology rapidly. Individually, many of the components of their system represent significant progress along predictable paths. For example, their electrodes, that they call threads, are very small and flexible; many researchers have tried to harness those properties to minimize the chance the brain’s immune response would reject the electrodes after insertion. Neuralink has also developed high-performance miniature electronics, another focus area for labs working on BMIs.

Often overlooked in academic settings, however, is how an entire system would be efficiently implanted in a brain.

Neuralink’s BMI requires brain surgery. This is because implanted electrodes that are in intimate contact with neurons will always outperform non-invasive electrodes where neurons are far away from the electrodes sitting outside the skull. So, a critical question becomes how to minimize the surgical challenges around getting the device into a brain.

Maybe the most impressive aspect of Neuralink’s announcement was that they created a 3,000-electrode neural interface where electrodes could be implanted at a rate of between 30 and 200 per minute. Each thread of electrodes is implanted by a sophisticated surgical robot that essentially acts like a sewing machine. This all happens while specifically avoiding blood vessels that blanket the surface of the brain. The robotics and imaging that enable this feat, with tight integration to the entire device, is striking.

Neuralink has thought through the challenge of developing a clinically viable BMI from beginning to end in a way that few groups have done, though they acknowledge that many challenges remain as they work towards getting this technology into human patients in the clinic.

Figuring Out What More Electrodes Gets You
The quest for implantable devices with thousands of electrodes is not only the domain of private companies. DARPA, the NIH BRAIN Initiative, and international consortiums are working on neurotechnologies for recording and stimulating in the brain with goals of tens of thousands of electrodes. But what might scientists do with the information from 1,000, 3,000, or maybe even 100,000 neurons?

At some level, devices with more electrodes might not actually be necessary to have a meaningful impact in people’s lives. Effective control of computers for access and communication, of robotic limbs to grasp and move objects as well as of paralyzed muscles is already happening—in people. And it has been for a number of years.

Since the 1990s, the Utah Array, which has just 100 electrodes and is manufactured by Blackrock Microsystems, has been a critical device in neuroscience and clinical research. This electrode array is FDA-cleared for temporary neural recording. Several research groups, including our own, have implanted Utah Arrays in people that lasted multiple years.

Currently, the biggest constraints are related to connectors, electronics, and system-level engineering, not the implanted electrode itself—although increasing the electrodes’ lifespan to more than five years would represent a significant advance. As those technical capabilities improve, it might turn out that the ability to accurately control computers and robots is limited more by scientists’ understanding of what the neurons are saying—that is, the neural code—than by the number of electrodes on the device.

Even the most capable implanted system, and maybe the most capable devices researchers can reasonably imagine, might fall short of the goal of actually augmenting skilled human performance. Nevertheless, Neuralink’s goal of creating better BMIs has the potential to improve the lives of people who can’t move or are unable to communicate. Right now, Musk’s vision of using BMIs to meld physical brains and intelligence with artificial ones is no more than a dream.

So, what does the future look like for Neuralink and other groups creating implantable BMIs? Devices with more electrodes that last longer and are connected to smaller and more powerful wireless electronics are essential. Better devices themselves, however, are insufficient. Continued public and private investment in companies and academic research labs, as well as innovative ways for these groups to work together to share technologies and data, will be necessary to truly advance scientists’ understanding of the brain and deliver on the promise of BMIs to improve peoples’ lives.

While researchers need to keep the future societal implications of advanced neurotechnologies in mind—there’s an essential role for ethicists and regulation—BMIs could be truly transformative as they help more people overcome limitations caused by injury or disease in the brain and body.

This article is republished from The Conversation under a Creative Commons license. Read the original article.

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