Tag Archives: style

#435793 Tiny Robots Carry Stem Cells Through a ...

Posted on September 21, 2019 by Android

Engineers have built microrobots to perform all sorts of tasks in the body, and can now add to that list another key skill: delivering stem cells. In a paper published today in Science Robotics, researchers describe propelling a magnetically-controlled, stem-cell-carrying bot through a live mouse.

Under a rotating magnetic field, the microrobots moved with rolling and corkscrew-style locomotion. The researchers, led by Hongsoo Choi and his team at the Daegu Gyeongbuk Institute of Science & Technology (DGIST), in South Korea, also demonstrated their bot’s moves in slices of mouse brain, in blood vessels isolated from rat brains, and in a multi-organ-on-a chip.

The invention provides an alternative way to deliver stem cells, which are increasingly important in medicine. Such cells can be coaxed into becoming nearly any kind of cell, making them great candidates for treating neurodegenerative disorders such as Alzheimer’s.

But delivering stem cells typically requires an injection with a needle, which lowers the survival rate of the stem cells, and limits their reach in the body. Microrobots, however, have the potential to deliver stem cells to precise, hard-to-reach areas, with less damage to surrounding tissue, and better survival rates, says Jin-young Kim, a principle investigator at DGIST-ETH Microrobotics Research Center, and an author on the paper.

The virtues of microrobots have inspired several research groups to propose and test different designs in simple conditions, such as microfluidic channels and other static environments. A group out of Hong Kong last year described a burr-shaped bot that carried cells through live, transparent zebrafish.

The new research presents a magnetically-actuated microrobot that successfully carried stem cells through a live mouse. In additional experiments, the cells, which had differentiated into brain cells such as astrocytes, oligodendrocytes, and neurons, transferred to microtissues on the multi-organ-on-a-chip. Taken together, the proof-of-concept experiments demonstrate the potential for microrobots to be used in human stem cell therapy, says Kim.

The team fabricated the robots with 3D laser lithography, and designed them in two shapes: spherical and helical. Using a rotating magnetic field, the scientists navigated the spherical-shaped bots with a rolling motion, and the helical bots with a corkscrew motion. These styles of locomotion proved more efficient than that from a simple pulling force, and were more suitable for use in biological fluids, the scientists reported.

The big challenge in navigating microbots in a live animal (or human body) is being able to see them in real time. Imaging with fMRI doesn’t work, because the magnetic fields interfere with the system. “To precisely control microbots in vivo, it is important to actually see them as they move,” the authors wrote in their paper.

That wasn’t possible during experiments in a live mouse, so the researchers had to check the location of the microrobots before and after the experiments using an optical tomography system called IVIS. They also had to resort to using a pulling force with a permanent magnet to navigate the microrobots inside the mouse, due to the limitations of the IVIS system.

Kim says he and his colleagues are developing imaging systems that will enable them to view in real time the locomotion of their microrobots in live animals. Continue reading →

Posted in Human Robots

#435664 Swarm Robots Mimic Ant Jaws to Flip and ...

Posted on September 15, 2019 by Android

Small robots are appealing because they’re simple, cheap, and it’s easy to make a lot of them. Unfortunately, being simple and cheap means that each robot individually can’t do a whole lot. To make up for this, you can do what insects do—leverage that simplicity and low-cost to just make a huge swarm of simple robots, and together, they can cooperate to carry out relatively complex tasks.

Using insects as an example does set a bit of an unfair expectation for the poor robots, since insects are (let’s be honest) generally smarter and much more versatile than a robot on their scale could ever hope to be. Most robots with insect-like capabilities (like DASH and its family) are really too big and complex to be turned into swarms, because to make a vast amount of small robots, things like motors aren’t going to work because they’re too expensive.

The question, then, is to how to make a swarm of inexpensive small robots with insect-like mobility that don’t need motors to get around, and Jamie Paik’s Reconfigurable Robotics Lab at EPFL has an answer, inspired by trap-jaw ants.

Let’s talk about trap-jaw ants for just a second, because they’re insane. You can read this 2006 paper about them if you’re particularly interested in insane ants (and who isn’t!), but if you just want to hear the insane bit, it’s that trap-jaw ants can fire themselves into the air by biting the ground (!). In just 0.06 millisecond, their half-millimeter long mandibles can close at a top speed of 64 meters per second, which works out to an acceleration of about 100,000 g’s. Biting the ground causes the ant’s head to snap back with a force of 300 times the body weight of the ant itself, which launches the ant upwards. The ants can fly 8 centimeters vertically, and up to 15 cm horizontally—this is a lot, for an ant that’s just a few millimeters long.

Trap-jaw ants can fire themselves into the air by biting the ground, causing the ant’s head to snap back with a force of 300 times the body weight of the ant itself

EPFL’s robots, called Tribots, look nothing at all like trap-jaw ants, which personally I am fine with. They’re about 5 cm tall, weighing 10 grams each, and can be built on a flat sheet, and then folded into a tripod shape, origami-style. Or maybe it’s kirigami, because there’s some cutting involved. The Tribots are fully autonomous, meaning they have onboard power and control, including proximity sensors that allow them to detect objects and avoid them.

Photo: Marc Delachaux/EPFL

EPFL researchers Zhenishbek Zhakypov and Jamie Paik.

Avoiding objects is where the trap-jaw ants come in. Using two different shape-memory actuators (a spring and a latch, similar to how the ant’s jaw works), the Tribots can move around using a bunch of different techniques that can adapt to the terrain that they’re on, including:

Vertical jumping for height
Horizontal jumping for distance
Somersault jumping to clear obstacles
Walking on textured terrain with short hops (called “flic-flac” walking)
Crawling on flat surfaces

Here’s the robot in action:

Tribot’s maximum vertical jump is 14 cm (2.5 times its height), and horizontally it can jump about 23 cm (almost 4 times its length). Tribot is actually quite efficient in these movements, with a cost of transport much lower than similarly-sized robots, on par with insects themselves.

Working together, small groups of Tribots can complete tasks that a single robot couldn’t do alone. One example is pushing a heavy object a set distance. It turns out that you need five Tribots for this task—a leader robot, two worker robots, a monitor robot to measure the distance that the object has been pushed, and then a messenger robot to relay communications around the obstacle.

Image: EPFL

Five Tribots collaborate to move an object to a desired position, using coordination between a leader, two workers, a monitor, and a messenger robot. The leader orders the two worker robots to push the object while the monitor measures the relative position of the object. As the object blocks the two-way link between the leader and the monitor, the messenger maintains the communication link.

The researchers acknowledge that the current version of the hardware is limited in pretty much every way (mobility, sensing, and computation), but it does a reasonable job of demonstrating what’s possible with the concept. The plan going forward is to automate fabrication in order to “enable on-demand, ’push-button-manufactured’” robots.

“Designing minimal and scalable insect-inspired multi-locomotion millirobots,” by Zhenishbek Zhakypov, Kazuaki Mori, Koh Hosoda, and Jamie Paik from EPFL and Osaka University, is published in the current issue of Nature.
[ RRL ] via [ EPFL ] Continue reading →

Posted in Human Robots

#435656 Will AI Be Fashion Forward—or a ...

Posted on September 15, 2019 by Android

The narrative that often accompanies most stories about artificial intelligence these days is how machines will disrupt any number of industries, from healthcare to transportation. It makes sense. After all, technology already drives many of the innovations in these sectors of the economy.

But sneakers and the red carpet? The definitively low-tech fashion industry would seem to be one of the last to turn over its creative direction to data scientists and machine learning algorithms.

However, big brands, e-commerce giants, and numerous startups are betting that AI can ingest data and spit out Chanel. Maybe it’s not surprising, given that fashion is partly about buzz and trends—and there’s nothing more buzzy and trendy in the world of tech today than AI.

In its annual survey of the $3 trillion fashion industry, consulting firm McKinsey predicted that while AI didn’t hit a “critical mass” in 2018, it would increasingly influence the business of everything from design to manufacturing.

“Fashion as an industry really has been so slow to understand its potential roles interwoven with technology. And, to be perfectly honest, the technology doesn’t take fashion seriously.” This comment comes from Zowie Broach, head of fashion at London’s Royal College of Arts, who as a self-described “old fashioned” designer has embraced the disruptive nature of technology—with some caveats.

Co-founder in the late 1990s of the avant-garde fashion label Boudicca, Broach has always seen tech as a tool for designers, even setting up a website for the company circa 1998, way before an online presence became, well, fashionable.

Broach told Singularity Hub that while she is generally optimistic about the future of technology in fashion—the designer has avidly been consuming old sci-fi novels over the last few years—there are still a lot of difficult questions to answer about the interface of algorithms, art, and apparel.

For instance, can AI do what the great designers of the past have done? Fashion was “about designing, it was about a narrative, it was about meaning, it was about expression,” according to Broach.

AI that designs products based on data gleaned from human behavior can potentially tap into the Pavlovian response in consumers in order to make money, Broach noted. But is that channeling creativity, or just digitally dabbling in basic human brain chemistry?

She is concerned about people retaining control of the process, whether we’re talking about their data or their designs. But being empowered with the insights machines could provide into, for example, the geographical nuances of fashion between Dubai, Moscow, and Toronto is thrilling.

“What is it that we want the future to be from a fashion, an identity, and design perspective?” she asked.

Off on the Right Foot
Silicon Valley and some of the biggest brands in the industry offer a few answers about where AI and fashion are headed (though not at the sort of depths that address Broach’s broader questions of aesthetics and ethics).

Take what is arguably the biggest brand in fashion, at least by market cap but probably not by the measure of appearances on Oscar night: Nike. The $100 billion shoe company just gobbled up an AI startup called Celect to bolster its data analytics and optimize its inventory. In other words, Nike hopes it will be able to figure out what’s hot and what’s not in a particular location to stock its stores more efficiently.

The company is going even further with Nike Fit, a foot-scanning platform using a smartphone camera that applies AI techniques from fields like computer vision and machine learning to find the best fit for each person’s foot. The algorithms then identify and recommend the appropriately sized and shaped shoe in different styles.

No doubt the next step will be to 3D print personalized and on-demand sneakers at any store.

San Francisco-based startup ThirdLove is trying to bring a similar approach to bra sizes. Its 20-member data team, Fortune reported, has developed the Fit Finder quiz that uses machine learning algorithms to help pick just the right garment for every body type.

Data scientists are also a big part of the team at Stitch Fix, a former San Francisco startup that went public in 2017 and today sports a market cap of more than $2 billion. The online “personal styling” company uses hundreds of algorithms to not only make recommendations to customers, but to help design new styles and even manage the subscription-based supply chain.

Future of Fashion
E-commerce giant Amazon has thrown its own considerable resources into developing AI applications for retail fashion—with mixed results.

One notable attempt involved a “styling assistant” that came with the company’s Echo Look camera that helped people catalog and manage their wardrobes, evening helping pick out each day’s attire. The company more recently revisited the direct consumer side of AI with an app called StyleSnap, which matches clothes and accessories uploaded to the site with the retailer’s vast inventory and recommends similar styles.

Behind the curtains, Amazon is going even further. A team of researchers in Israel have developed algorithms that can deduce whether a particular look is stylish based on a few labeled images. Another group at the company’s San Francisco research center was working on tech that could generate new designs of items based on images of a particular style the algorithms trained on.

“I will say that the accumulation of many new technologies across the industry could manifest in a highly specialized style assistant, far better than the examples we’ve seen today. However, the most likely thing is that the least sexy of the machine learning work will become the most impactful, and the public may never hear about it.”

That prediction is from an online interview with Leanne Luce, a fashion technology blogger and product manager at Google who recently wrote a book called, succinctly enough, Artificial Intelligence and Fashion.

Data Meets Design
Academics are also sticking their beakers into AI and fashion. Researchers at the University of California, San Diego, and Adobe Research have previously demonstrated that neural networks, a type of AI designed to mimic some aspects of the human brain, can be trained to generate (i.e., design) new product images to match a buyer’s preference, much like the team at Amazon.

Meanwhile, scientists at Hong Kong Polytechnic University are working with China’s answer to Amazon, Alibaba, on developing a FashionAI Dataset to help machines better understand fashion. The effort will focus on how algorithms approach certain building blocks of design, what are called “key points” such as neckline and waistline, and “fashion attributes” like collar types and skirt styles.

The man largely behind the university’s research team is Calvin Wong, a professor and associate head of Hong Kong Polytechnic University’s Institute of Textiles and Clothing. His group has also developed an “intelligent fabric defect detection system” called WiseEye for quality control, reducing the chance of producing substandard fabric by 90 percent.

Wong and company also recently inked an agreement with RCA to establish an AI-powered design laboratory, though the details of that venture have yet to be worked out, according to Broach.

One hope is that such collaborations will not just get at the technological challenges of using machines in creative endeavors like fashion, but will also address the more personal relationships humans have with their machines.

“I think who we are, and how we use AI in fashion, as our identity, is not a superficial skin. It’s very, very important for how we define our future,” Broach said.

Image Credit: Inspirationfeed / Unsplash Continue reading →

Posted in Human Robots

#435579 RoMeLa’s Newest Robot Is a ...

Posted on September 11, 2019 by Android

A few years ago, we wrote about NABiRoS, a bipedal robot from Dennis Hong’s Robotics & Mechanisms Laboratory (RoMeLa) at UCLA. Unlike pretty much any other biped we’d ever seen, NABiRoS had a unique kinematic configuration that had it using its two legs to walk sideways, which offered some surprising advantages.

As it turns out, bipeds aren’t the only robots that can potentially benefit from a bit of a kinematic rethink. RoMeLa has redesigned quadrupedal robots too—rather than model them after a quadrupedal animal like a dog or a horse, RoMeLa’s ALPHRED robots use four legs arranged symmetrically around the body of the robot, allowing it to walk, run, hop, and jump, as well as manipulate and carry objects, karate chop through boards, and even roller skate on its butt. This robot can do it all.

Impressive, right? This is ALPHRED 2, and its predecessor, the original ALPHRED, was introduced at IROS 2018. Both ALPHREDs are axisymmetric about the vertical axis, meaning that they don’t have a front or a back and are perfectly happy to walk in any direction you like. Traditional quadrupeds like Spot or Laikago can also move sideways and backwards, but their leg arrangement makes them more efficient at moving in one particular direction, and also results in some curious compromises like a preference for going down stairs backwards. ANYmal is a bit more flexible in that it can reverse its knees, but it’s still got that traditional quadrupedal two-by-two configuration.

ALPHRED 2’s four symmetrical limbs can be used for a whole bunch of stuff. It can do quadrupedal walking and running, and it’s able to reach stable speeds of up to 1.5 m/s. If you want bipedal walking, it can do that NABiRoS-style, although it’s still a bit fragile at the moment. Using two legs for walking leaves two legs free, and those legs can turn into arms. A tripedal compromise configuration, with three legs and one arm, is more stable and allows the robot to do things like push buttons, open doors, and destroy property. And thanks to passive wheels under its body, ALPHRED 2 can use its limbs to quickly and efficiently skate around:

The impressive performance of the robot comes courtesy of a custom actuator that RoMeLa designed specifically for dynamic legged locomotion. They call it BEAR, or Back-Drivable Electromechanical Actuator for Robots. These are optionally liquid-cooled motors capable of proprioceptive sensing, consisting of a DC motor, a single stage 10:1 planetary gearbox, and channels through the back of the housing that coolant can be pumped through. The actuators have a peak torque of 32 Nm, and a continuous torque of about 8 Nm with passive air cooling. With liquid cooling, the continuous torque jumps to about 21 Nm. And in the videos above, ALPHRED 2 isn’t even running the liquid cooling system, suggesting that it’s capable of much higher sustained performance.

Photo: RoMeLa

Using two legs for walking leaves two legs free, and those legs can turn into arms.

RoMeLa has produced a bunch of very creative robots, and we appreciate that they also seem to produce a bunch of very creative demos showing why their unusual approaches are in fact (at least in some specific cases) somewhat practical. With the recent interest in highly dynamic robots that can be reliably useful in environments infested with humans, we can’t wait to see what kinds of exciting tricks the next (presumably liquid-cooled) version will be able to do.

[ RoMeLa ] Continue reading →

Posted in Human Robots

#435522 Harvard’s Smart Exo-Shorts Talk to the ...

Posted on August 20, 2019 by Android

Exosuits don’t generally scream “fashionable” or “svelte.” Take the mind-controlled robotic exoskeleton that allowed a paraplegic man to kick off the World Cup back in 2014. Is it cool? Hell yeah. Is it practical? Not so much.

Yapping about wearability might seem childish when the technology already helps people with impaired mobility move around dexterously. But the lesson of the ill-fated Google Glassholes, which includes an awkward dorky head tilt and an assuming voice command, clearly shows that wearable computer assistants can’t just work technologically—they have to look natural and allow the user to behave like as usual. They have to, in a sense, disappear.

To Dr. Jose Pons at the Legs + Walking Ability Lab in Chicago, exosuits need three main selling points to make it in the real world. One, they have to physically interact with their wearer and seamlessly deliver assistance when needed. Two, they should cognitively interact with the host to guide and control the robot at all times. Finally, they need to feel like a second skin—move with the user without adding too much extra mass or reducing mobility.

This week, a US-Korean collaboration delivered the whole shebang in a Lululemon-style skin-hugging package combined with a retro waist pack. The portable exosuit, weighing only 11 pounds, looks like a pair of spandex shorts but can support the wearer’s hip movement when needed. Unlike their predecessors, the shorts are embedded with sensors that let them know when the wearer is walking versus running by analyzing gait.

Switching between the two movement modes may not seem like much, but what naturally comes to our brains doesn’t translate directly to smart exosuits. “Walking and running have fundamentally different biomechanics, which makes developing devices that assist both gaits challenging,” the team said. Their algorithm, computed in the cloud, allows the wearer to easily switch between both, with the shorts providing appropriate hip support that makes the movement experience seamless.

To Pons, who was not involved in the research but wrote a perspective piece, the study is an exciting step towards future exosuits that will eventually disappear under the skin—that is, implanted neural interfaces to control robotic assistance or activate the user’s own muscles.

“It is realistic to think that we will witness, in the next several years…robust human-robot interfaces to command wearable robotics based on…the neural code of movement in humans,” he said.

A “Smart” Exosuit Hack
There are a few ways you can hack a human body to move with an exosuit. One is using implanted electrodes inside the brain or muscles to decipher movement intent. With heavy practice, a neural implant can help paralyzed people walk again or dexterously move external robotic arms. But because the technique requires surgery, it’s not an immediate sell for people who experience low mobility because of aging or low muscle tone.

The other approach is to look to biophysics. Rather than decoding neural signals that control movement, here the idea is to measure gait and other physical positions in space to decipher intent. As you can probably guess, accurately deciphering user intent isn’t easy, especially when the wearable tries to accommodate multiple gaits. But the gains are many: there’s no surgery involved, and the wearable is low in energy consumption.

Double Trouble
The authors decided to tackle an everyday situation. You’re walking to catch the train to work, realize you’re late, and immediately start sprinting.

That seemingly easy conversion hides a complex switch in biomechanics. When you walk, your legs act like an inverted pendulum that swing towards a dedicated center in a predictable way. When you run, however, the legs move more like a spring-loaded system, and the joints involved in the motion differ from a casual stroll. Engineering an assistive wearable for each is relatively simple; making one for both is exceedingly hard.

Led by Dr. Conor Walsh at Harvard University, the team started with an intuitive idea: assisted walking and running requires specialized “actuation” profiles tailored to both. When the user is moving in a way that doesn’t require assistance, the wearable needs to be out of the way so that it doesn’t restrict mobility. A quick analysis found that assisting hip extension has the largest impact, because it’s important to both gaits and doesn’t add mass to the lower legs.

Building on that insight, the team made a waist belt connected to two thigh wraps, similar to a climbing harness. Two electrical motors embedded inside the device connect the waist belt to other components through a pulley system to help the hip joints move. The whole contraption weighed about 11 lbs and didn’t obstruct natural movement.

Next, the team programmed two separate supporting profiles for walking and running. The goal was to reduce the “metabolic cost” for both movements, so that the wearer expends as little energy as needed. To switch between the two programs, they used a cloud-based classification algorithm to measure changes in energy fluctuation to figure out what mode—running or walking—the user is in.

Smart Booster
Initial trials on treadmills were highly positive. Six male volunteers with similar age and build donned the exosuit and either ran or walked on the treadmill at varying inclines. The algorithm performed perfectly at distinguishing between the two gaits in all conditions, even at steep angles.

An outdoor test with eight volunteers also proved the algorithm nearly perfect. Even on uneven terrain, only two steps out of all test trials were misclassified. In an additional trial on mud or snow, the algorithm performed just as well.

“The system allows the wearer to use their preferred gait for each speed,” the team said.

Software excellence translated to performance. A test found that the exosuit reduced the energy for walking by over nine percent and running by four percent. It may not sound like much, but the range of improvement is meaningful in athletic performance. Putting things into perspective, the team said, the metabolic rate reduction during walking is similar to taking 16 pounds off at the waist.

The Wearable Exosuit Revolution
The study’s lightweight exoshorts are hardly the only players in town. Back in 2017, SRI International’s spin-off, Superflex, engineered an Aura suit to support mobility in the elderly. The Aura used a different mechanism: rather than a pulley system, it incorporated a type of smart material that contracts in a manner similar to human muscles when zapped with electricity.

Embedded with a myriad of sensors for motion, accelerometers and gyroscopes, Aura’s smartness came from mini-computers that measure how fast the wearer is moving and track the user’s posture. The data were integrated and processed locally inside hexagon-shaped computing pods near the thighs and upper back. The pods also acted as the control center for sending electrical zaps to give the wearer a boost when needed.

Around the same time, a collaboration between Harvard’s Wyss Institute and ReWalk Robotics introduced a fabric-based wearable robot to assist a wearer’s legs for balance and movement. Meanwhile, a Swiss team coated normal fabric with electroactive material to weave soft, pliable artificial “muscles” that move with the skin.

Although health support is the current goal, the military is obviously interested in similar technologies to enhance soldiers’ physicality. Superflex’s Aura, for example, was originally inspired by technology born from DARPA’s Warrior Web Program, which aimed to reduce a soldier’s mechanical load.

That said, military gear has had a long history of trickling down to consumer use. Similar to the way camouflage, cargo pants, and GORE-TEX trickled down into the consumer ecosphere, it’s not hard to imagine your local Target eventually stocking intelligent exowear.

Image and Video Credit: Wyss Institute at Harvard University. Continue reading →

Posted in Human Robots