Tag Archives: german

#435626 Video Friday: Watch Robots Make a Crepe ...

Video Friday is your weekly selection of awesome robotics videos, collected by your Automaton bloggers. Every week, we also post a calendar of upcoming robotics events; here's what we have so far (send us your events!):

Robotronica – August 18, 2019 – Brisbane, Australia
CLAWAR 2019 – August 26-28, 2019 – Kuala Lumpur, Malaysia
IEEE Africon 2019 – September 25-27, 2019 – Accra, Ghana
ISRR 2019 – October 6-10, 2019 – Hanoi, Vietnam
Ro-Man 2019 – October 14-18, 2019 – New Delhi
Humanoids 2019 – October 15-17, 2019 – Toronto
ARSO 2019 – October 31-November 2, 2019 – Beijing
ROSCon 2019 – October 31-November 1, 2019 – Macau
IROS 2019 – November 4-8, 2019 – Macau
Let us know if you have suggestions for next week, and enjoy today's videos.

Team CoSTAR (JPL, MIT, Caltech, KAIST, LTU) has one of the more diverse teams of robots that we’ve seen:

[ Team CoSTAR ]

A team from Carnegie Mellon University and Oregon State University is sending ground and aerial autonomous robots into a Pittsburgh-area mine to prepare for this month’s DARPA Subterranean Challenge.

“Look at that fire extinguisher, what a beauty!” Expect to hear a lot more of that kind of weirdness during SubT.

[ CMU ]

Unitree Robotics is starting to batch-manufacture Laikago Pro quadrupeds, and if you buy four of them, they can carry you around in a chair!

I’m also really liking these videos from companies that are like, “We have a whole bunch of robot dogs now—what weird stuff can we do with them?”

[ Unitree Robotics ]

Why take a handful of pills every day for all the stuff that's wrong with you, when you could take one custom pill instead? Because custom pills are time-consuming to make, that’s why. But robots don’t care!

Multiply Labs’ factory is designed to operate in parallel. All the filling robots and all the quality-control robots are operating at the same time. The robotic arm, in the meanwhile, shuttles dozens of trays up and down the production floor, making sure that each capsule is filled with the right drugs. The manufacturing cell shown in this article can produce 10,000 personalized capsules in an 8-hour shift. A single cell occupies just 128 square feet (12 square meters) on the production floor. This means that a regular production facility (~10,000 square feet, or 929 m2 ) can house 78 cells, for an overall output of 780,000 capsules per shift. This exceeds the output of most traditional manufacturers—while producing unique personalized capsules!

[ Multiply Labs ]

Thanks Fred!

If you’re getting tired of all those annoying drones that sound like giant bees, just have a listen to this turbine-powered one:

[ Malloy Aeronautics ]

In retrospect, it’s kind of amazing that nobody has bothered to put a functional robotic dog head on a quadruped robot before this, right?

Equipped with sensors, high-tech radar imaging, cameras and a directional microphone, this 100-pound (45-kilogram) super-robot is still a “puppy-in-training.” Just like a regular dog, he responds to commands such as “sit,” “stand,” and “lie down.” Eventually, he will be able to understand and respond to hand signals, detect different colors, comprehend many languages, coordinate his efforts with drones, distinguish human faces, and even recognize other dogs.

As an information scout, Astro’s key missions will include detecting guns, explosives and gun residue to assist police, the military, and security personnel. This robodog’s talents won’t just end there, he also can be programmed to assist as a service dog for the visually impaired or to provide medical diagnostic monitoring. The MPCR team also is training Astro to serve as a first responder for search-and-rescue missions such as hurricane reconnaissance as well as military maneuvers.

[ FAU ]

And now this amazing video, “The Coke Thief,” from ICRA 2005 (!):

[ Paper ]

CYBATHLON Series put the focus on one or two of the six disciplines and are organized in cooperation with international universities and partners. The CYBATHLON Arm and Leg Prosthesis Series took place in Karlsruhe, Germany, from 16 to 18 May and was organized in cooperation with the Karlsruhe Institute of Technology (KIT) and the trade fair REHAB Karlsruhe.

The CYBATHLON Wheelchair Series took place in Kawasaki, Japan on 5 May 2019 and was organized in cooperation with the CYBATHLON Wheelchair Series Japan Organizing Committee and supported by the Swiss Embassy.

[ Cybathlon ]

Rainbow crepe robot!

There’s also this other robot, which I assume does something besides what's in the video, because otherwise it appears to be a massively overengineered way of shaping cooked rice into a chubby triangle.

[ PC Watch ]

The Weaponized Plastic Fighting League at Fetch Robotics has had another season of shardation, deintegration, explodification, and other -tions. Here are a couple fan favorite match videos:

[ Fetch Robotics ]

This video is in German, but it’s worth watching for the three seconds of extremely satisfying footage showing a robot twisting dough into pretzels.

[ Festo ]

Putting brains into farming equipment is a no-brainer, since it’s a semi-structured environment that's generally clear of wayward humans driving other vehicles.

[ Lovol ]

Thanks Fan!

Watch some robots assemble suspiciously Lego-like (but definitely not actually Lego) minifigs.

[ DevLinks ]

The Robotics Innovation Facility (RIFBristol) helps businesses, entrepreneurs, researchers and public sector bodies to embrace the concept of ‘Industry 4.0'. From training your staff in robotics, and demonstrating how automation can improve your manufacturing processes, to prototyping and validating your new innovations—we can provide the support you need.

[ RIF ]

Ryan Gariepy from Clearpath Robotics (and a bunch of other stuff) gave a talk at ICRA with the title of “Move Fast and (Don’t) Break Things: Commercializing Robotics at the Speed of Venture Capital,” which is more interesting when you know that this year’s theme was “Notable Failures.”

[ Clearpath Robotics ]

In this week’s episode of Robots in Depth, Per interviews Michael Nielsen, a computer vision researcher at the Danish Technological Institute.

Michael worked with a fusion of sensors like stereo vision, thermography, radar, lidar and high-frame-rate cameras, merging multiple images for high dynamic range. All this, to be able to navigate the tricky situation in a farm field where you need to navigate close to or even in what is grown. Multibaseline cameras were also used to provide range detection over a wide range of distances.

We also learn about how he expanded his work into sorting recycling, a very challenging problem. We also hear about the problems faced when using time of flight and sheet of light cameras. He then shares some good results using stereo vision, especially combined with blue light random dot projectors.

[ Robots in Depth ] Continue reading

Posted in Human Robots

#435535 This Week’s Awesome Tech Stories From ...

ARTIFICIAL INTELLIGENCE
To Power AI, This Startup Built a Really, Really Big Chip
Tom Simonite | Wired
“The silicon monster is almost 22 centimeters—roughly 9 inches—on each side, making it likely the largest computer chip ever, and a monument to the tech industry’s hopes for artificial intelligence.”

COMPUTING
You Won’t See the Quantum Internet Coming
Ryan F. Mandelbaum | Gizmodo
“The quantum internet is coming sooner than you think—even sooner than quantum computing itself. When things change over, you might not even notice. But when they do, new rules will protect your data against attacks from computers that don’t even exist yet.”

LONGEVITY
What If Aging Weren’t Inevitable, But a Curable Disease
David Adam | MIT Technology Review
“…a growing number of scientists are questioning our basic conception of aging. What if you could challenge your death—or even prevent it altogether? What if the panoply of diseases that strike us in old age are symptoms, not causes? What would change if we classified aging itself as the disease?”

ROBOTICS
Thousands of Autonomous Delivery Robots Are About to Descend on College Campuses
Andrew J. Hawkins | The Verge
“The quintessential college experience of getting pizza delivered to your dorm room is about to get a high-tech upgrade. On Tuesday, Starship Technologies announced its plan to deploy thousands of its autonomous six-wheeled delivery robots on college campuses around the country over the next two years, after raising $40 million in Series A funding.”

TRANSPORTATION
Volocopter Reveals Its First Commercial Autonomous Flying Taxi
Christine Fisher | Endgadget
“It’s a race to the skies in terms of which company actually deploys an on-demand air taxi service based around electric vertical take-off and landing aircraft. For its part, German startup Volocopter is taking another key step with the revelation of its first aircraft designed for actual commercial use, the VoloCity.”

Image Credit: Colin Carter / Unsplash Continue reading

Posted in Human Robots

#434786 AI Performed Like a Human on a Gestalt ...

Dr. Been Kim wants to rip open the black box of deep learning.

A senior researcher at Google Brain, Kim specializes in a sort of AI psychology. Like cognitive psychologists before her, she develops various ways to probe the alien minds of artificial neural networks (ANNs), digging into their gory details to better understand the models and their responses to inputs.

The more interpretable ANNs are, the reasoning goes, the easier it is to reveal potential flaws in their reasoning. And if we understand when or why our systems choke, we’ll know when not to use them—a foundation for building responsible AI.

There are already several ways to tap into ANN reasoning, but Kim’s inspiration for unraveling the AI black box came from an entirely different field: cognitive psychology. The field aims to discover fundamental rules of how the human mind—essentially also a tantalizing black box—operates, Kim wrote with her colleagues.

In a new paper uploaded to the pre-publication server arXiv, the team described a way to essentially perform a human cognitive test on ANNs. The test probes how we automatically complete gaps in what we see, so that they form entire objects—for example, perceiving a circle from a bunch of loose dots arranged along a clock face. Psychologist dub this the “law of completion,” a highly influential idea that led to explanations of how our minds generalize data into concepts.

Because deep neural networks in machine vision loosely mimic the structure and connections of the visual cortex, the authors naturally asked: do ANNs also exhibit the law of completion? And what does that tell us about how an AI thinks?

Enter the Germans
The law of completion is part of a series of ideas from Gestalt psychology. Back in the 1920s, long before the advent of modern neuroscience, a group of German experimental psychologists asked: in this chaotic, flashy, unpredictable world, how do we piece together input in a way that leads to meaningful perceptions?

The result is a group of principles known together as the Gestalt effect: that the mind self-organizes to form a global whole. In the more famous words of Gestalt psychologist Kurt Koffka, our perception forms a whole that’s “something else than the sum of its parts.” Not greater than; just different.

Although the theory has its critics, subsequent studies in humans and animals suggest that the law of completion happens on both the cognitive and neuroanatomical level.

Take a look at the drawing below. You immediately “see” a shape that’s actually the negative: a triangle or a square (A and B). Or you further perceive a 3D ball (C), or a snake-like squiggle (D). Your mind fills in blank spots, so that the final perception is more than just the black shapes you’re explicitly given.

Image Credit: Wikimedia Commons contributors, the free media repository.
Neuroscientists now think that the effect comes from how our visual system processes information. Arranged in multiple layers and columns, lower-level neurons—those first to wrangle the data—tend to extract simpler features such as lines or angles. In Gestalt speak, they “see” the parts.

Then, layer by layer, perception becomes more abstract, until higher levels of the visual system directly interpret faces or objects—or things that don’t really exist. That is, the “whole” emerges.

The Experiment Setup
Inspired by these classical experiments, Kim and team developed a protocol to test the Gestalt effect on feed-forward ANNs: one simple, the other, dubbed the “Inception V3,” far more complex and widely used in the machine vision community.

The main idea is similar to the triangle drawings above. First, the team generated three datasets: one set shows complete, ordinary triangles. The second—the “Illusory” set, shows triangles with the edges removed but the corners intact. Thanks to the Gestalt effect, to us humans these generally still look like triangles. The third set also only shows incomplete triangle corners. But here, the corners are randomly rotated so that we can no longer imagine a line connecting them—hence, no more triangle.

To generate a dataset large enough to tease out small effects, the authors changed the background color, image rotation, and other aspects of the dataset. In all, they produced nearly 1,000 images to test their ANNs on.

“At a high level, we compare an ANN’s activation similarities between the three sets of stimuli,” the authors explained. The process is two steps: first, train the AI on complete triangles. Second, test them on the datasets. If the response is more similar between the illusory set and the complete triangle—rather than the randomly rotated set—it should suggest a sort of Gestalt closure effect in the network.

Machine Gestalt
Right off the bat, the team got their answer: yes, ANNs do seem to exhibit the law of closure.

When trained on natural images, the networks better classified the illusory set as triangles than those with randomized connection weights or networks trained on white noise.

When the team dug into the “why,” things got more interesting. The ability to complete an image correlated with the network’s ability to generalize.

Humans subconsciously do this constantly: anything with a handle made out of ceramic, regardless of shape, could easily be a mug. ANNs still struggle to grasp common features—clues that immediately tells us “hey, that’s a mug!” But when they do, it sometimes allows the networks to better generalize.

“What we observe here is that a network that is able to generalize exhibits…more of the closure effect [emphasis theirs], hinting that the closure effect reflects something beyond simply learning features,” the team wrote.

What’s more, remarkably similar to the visual cortex, “higher” levels of the ANNs showed more of the closure effect than lower layers, and—perhaps unsurprisingly—the more layers a network had, the more it exhibited the closure effect.

As the networks learned, their ability to map out objects from fragments also improved. When the team messed around with the brightness and contrast of the images, the AI still learned to see the forest from the trees.

“Our findings suggest that neural networks trained with natural images do exhibit closure,” the team concluded.

AI Psychology
That’s not to say that ANNs recapitulate the human brain. As Google’s Deep Dream, an effort to coax AIs into spilling what they’re perceiving, clearly demonstrates, machine vision sees some truly weird stuff.

In contrast, because they’re modeled after the human visual cortex, perhaps it’s not all that surprising that these networks also exhibit higher-level properties inherent to how we process information.

But to Kim and her colleagues, that’s exactly the point.

“The field of psychology has developed useful tools and insights to study human brains– tools that we may be able to borrow to analyze artificial neural networks,” they wrote.

By tweaking these tools to better analyze machine minds, the authors were able to gain insight on how similarly or differently they see the world from us. And that’s the crux: the point isn’t to say that ANNs perceive the world sort of, kind of, maybe similar to humans. It’s to tap into a wealth of cognitive psychology tools, established over decades using human minds, to probe that of ANNs.

“The work here is just one step along a much longer path,” the authors conclude.

“Understanding where humans and neural networks differ will be helpful for research on interpretability by enlightening the fundamental differences between the two interesting species.”

Image Credit: Popova Alena / Shutterstock.com Continue reading

Posted in Human Robots

#434569 From Parkour to Surgery, Here Are the ...

The robot revolution may not be here quite yet, but our mechanical cousins have made some serious strides. And now some of the leading experts in the field have provided a rundown of what they see as the 10 most exciting recent developments.

Compiled by the editors of the journal Science Robotics, the list includes some of the most impressive original research and innovative commercial products to make a splash in 2018, as well as a couple from 2017 that really changed the game.

1. Boston Dynamics’ Atlas doing parkour

It seems like barely a few months go by without Boston Dynamics rewriting the book on what a robot can and can’t do. Last year they really outdid themselves when they got their Atlas humanoid robot to do parkour, leaping over logs and jumping between wooden crates.

Atlas’s creators have admitted that the videos we see are cherry-picked from multiple attempts, many of which don’t go so well. But they say they’re meant to be inspirational and aspirational rather than an accurate picture of where robotics is today. And combined with the company’s dog-like Spot robot, they are certainly pushing boundaries.

2. Intuitive Surgical’s da Vinci SP platform
Robotic surgery isn’t new, but the technology is improving rapidly. Market leader Intuitive’s da Vinci surgical robot was first cleared by the FDA in 2000, but since then it’s come a long way, with the company now producing three separate systems.

The latest addition is the da Vinci SP (single port) system, which is able to insert three instruments into the body through a single 2.5cm cannula (tube) bringing a whole new meaning to minimally invasive surgery. The system was granted FDA clearance for urological procedures last year, and the company has now started shipping the new system to customers.

3. Soft robot that navigates through growth

Roboticists have long borrowed principles from the animal kingdom, but a new robot design that mimics the way plant tendrils and fungi mycelium move by growing at the tip has really broken the mold on robot navigation.

The editors point out that this is the perfect example of bio-inspired design; the researchers didn’t simply copy nature, they took a general principle and expanded on it. The tube-like robot unfolds from the front as pneumatic pressure is applied, but unlike a plant, it can grow at the speed of an animal walking and can navigate using visual feedback from a camera.

4. 3D printed liquid crystal elastomers for soft robotics
Soft robotics is one of the fastest-growing sub-disciplines in the field, but powering these devices without rigid motors or pumps is an ongoing challenge. A variety of shape-shifting materials have been proposed as potential artificial muscles, including liquid crystal elastomeric actuators.

Harvard engineers have now demonstrated that these materials can be 3D printed using a special ink that allows the designer to easily program in all kinds of unusual shape-shifting abilities. What’s more, their technique produces actuators capable of lifting significantly more weight than previous approaches.

5. Muscle-mimetic, self-healing, and hydraulically amplified actuators
In another effort to find a way to power soft robots, last year researchers at the University of Colorado Boulder designed a series of super low-cost artificial muscles that can lift 200 times their own weight and even heal themselves.

The devices rely on pouches filled with a liquid that makes them contract with the force and speed of mammalian skeletal muscles when a voltage is applied. The most promising for robotics applications is the so-called Peano-HASEL, which features multiple rectangular pouches connected in series that contract linearly, just like real muscle.

6. Self-assembled nanoscale robot from DNA

While you may think of robots as hulking metallic machines, a substantial number of scientists are working on making nanoscale robots out of DNA. And last year German researchers built the first remote-controlled DNA robotic arm.

They created a length of tightly-bound DNA molecules to act as the arm and attached it to a DNA base plate via a flexible joint. Because DNA carries a charge, they were able to get the arm to swivel around like the hand of a clock by applying a voltage and switch direction by reversing that voltage. The hope is that this arm could eventually be used to build materials piece by piece at the nanoscale.

7. DelFly nimble bioinspired robotic flapper

Robotics doesn’t only borrow from biology—sometimes it gives back to it, too. And a new flapping-winged robot designed by Dutch engineers that mimics the humble fruit fly has done just that, by revealing how the animals that inspired it carry out predator-dodging maneuvers.

The lab has been building flapping robots for years, but this time they ditched the airplane-like tail used to control previous incarnations. Instead, they used insect-inspired adjustments to the motions of its twin pairs of flapping wings to hover, pitch, and roll with the agility of a fruit fly. That has provided a useful platform for investigating insect flight dynamics, as well as more practical applications.

8. Soft exosuit wearable robot

Exoskeletons could prevent workplace injuries, help people walk again, and even boost soldiers’ endurance. Strapping on bulky equipment isn’t ideal, though, so researchers at Harvard are working on a soft exoskeleton that combines specially-designed textiles, sensors, and lightweight actuators.

And last year the team made an important breakthrough by combining their novel exoskeleton with a machine-learning algorithm that automatically tunes the device to the user’s particular walking style. Using physiological data, it is able to adjust when and where the device needs to deliver a boost to the user’s natural movements to improve walking efficiency.

9. Universal Robots (UR) e-Series Cobots
Robots in factories are nothing new. The enormous mechanical arms you see in car factories normally have to be kept in cages to prevent them from accidentally crushing people. In recent years there’s been growing interest in “co-bots,” collaborative robots designed to work side-by-side with their human colleagues and even learn from them.

Earlier this year saw the demise of ReThink robotics, the pioneer of the approach. But the simple single arm devices made by Danish firm Universal Robotics are becoming ubiquitous in workshops and warehouses around the world, accounting for about half of global co-bot sales. Last year they released their latest e-Series, with enhanced safety features and force/torque sensing.

10. Sony’s aibo
After a nearly 20-year hiatus, Sony’s robotic dog aibo is back, and it’s had some serious upgrades. As well as a revamp to its appearance, the new robotic pet takes advantage of advances in AI, with improved environmental and command awareness and the ability to develop a unique character based on interactions with its owner.

The editors note that this new context awareness mark the device out as a significant evolution in social robots, which many hope could aid in childhood learning or provide companionship for the elderly.

Image Credit: DelFly Nimble / CC BY – SA 4.0 Continue reading

Posted in Human Robots

#433954 The Next Great Leap Forward? Combining ...

The Internet of Things is a popular vision of objects with internet connections sending information back and forth to make our lives easier and more comfortable. It’s emerging in our homes, through everything from voice-controlled speakers to smart temperature sensors. To improve our fitness, smart watches and Fitbits are telling online apps how much we’re moving around. And across entire cities, interconnected devices are doing everything from increasing the efficiency of transport to flood detection.

In parallel, robots are steadily moving outside the confines of factory lines. They’re starting to appear as guides in shopping malls and cruise ships, for instance. As prices fall and the artificial intelligence (AI) and mechanical technology continues to improve, we will get more and more used to them making independent decisions in our homes, streets and workplaces.

Here lies a major opportunity. Robots become considerably more capable with internet connections. There is a growing view that the next evolution of the Internet of Things will be to incorporate them into the network, opening up thrilling possibilities along the way.

Home Improvements
Even simple robots become useful when connected to the internet—getting updates about their environment from sensors, say, or learning about their users’ whereabouts and the status of appliances in the vicinity. This lets them lend their bodies, eyes, and ears to give an otherwise impersonal smart environment a user-friendly persona. This can be particularly helpful for people at home who are older or have disabilities.

We recently unveiled a futuristic apartment at Heriot-Watt University to work on such possibilities. One of a few such test sites around the EU, our whole focus is around people with special needs—and how robots can help them by interacting with connected devices in a smart home.

Suppose a doorbell rings that has smart video features. A robot could find the person in the home by accessing their location via sensors, then tell them who is at the door and why. Or it could help make video calls to family members or a professional carer—including allowing them to make virtual visits by acting as a telepresence platform.

Equally, it could offer protection. It could inform them the oven has been left on, for example—phones or tablets are less reliable for such tasks because they can be misplaced or not heard.

Similarly, the robot could raise the alarm if its user appears to be in difficulty.Of course, voice-assistant devices like Alexa or Google Home can offer some of the same services. But robots are far better at moving, sensing and interacting with their environment. They can also engage their users by pointing at objects or acting more naturally, using gestures or facial expressions. These “social abilities” create bonds which are crucially important for making users more accepting of the support and making it more effective.

To help incentivize the various EU test sites, our apartment also hosts the likes of the European Robotic League Service Robot Competition—a sort of Champions League for robots geared to special needs in the home. This brought academics from around Europe to our laboratory for the first time in January this year. Their robots were tested in tasks like welcoming visitors to the home, turning the oven off, and fetching objects for their users; and a German team from Koblenz University won with a robot called Lisa.

Robots Offshore
There are comparable opportunities in the business world. Oil and gas companies are looking at the Internet of Things, for example; experimenting with wireless sensors to collect information such as temperature, pressure, and corrosion levels to detect and possibly predict faults in their offshore equipment.

In the future, robots could be alerted to problem areas by sensors to go and check the integrity of pipes and wells, and to make sure they are operating as efficiently and safely as possible. Or they could place sensors in parts of offshore equipment that are hard to reach, or help to calibrate them or replace their batteries.

The likes of the ORCA Hub, a £36m project led by the Edinburgh Centre for Robotics, bringing together leading experts and over 30 industry partners, is developing such systems. The aim is to reduce the costs and the risks of humans working in remote hazardous locations.

ORCA tests a drone robot. ORCA
Working underwater is particularly challenging, since radio waves don’t move well under the sea. Underwater autonomous vehicles and sensors usually communicate using acoustic waves, which are many times slower (1,500 meters a second vs. 300m meters a second for radio waves). Acoustic communication devices are also much more expensive than those used above the water.

This academic project is developing a new generation of low-cost acoustic communication devices, and trying to make underwater sensor networks more efficient. It should help sensors and underwater autonomous vehicles to do more together in future—repair and maintenance work similar to what is already possible above the water, plus other benefits such as helping vehicles to communicate with one another over longer distances and tracking their location.

Beyond oil and gas, there is similar potential in sector after sector. There are equivalents in nuclear power, for instance, and in cleaning and maintaining the likes of bridges and buildings. My colleagues and I are also looking at possibilities in areas such as farming, manufacturing, logistics, and waste.

First, however, the research sectors around the Internet of Things and robotics need to properly share their knowledge and expertise. They are often isolated from one another in different academic fields. There needs to be more effort to create a joint community, such as the dedicated workshops for such collaboration that we organized at the European Robotics Forum and the IoT Week in 2017.

To the same end, industry and universities need to look at setting up joint research projects. It is particularly important to address safety and security issues—hackers taking control of a robot and using it to spy or cause damage, for example. Such issues could make customers wary and ruin a market opportunity.

We also need systems that can work together, rather than in isolated applications. That way, new and more useful services can be quickly and effectively introduced with no disruption to existing ones. If we can solve such problems and unite robotics and the Internet of Things, it genuinely has the potential to change the world.

Mauro Dragone, Assistant Professor, Cognitive Robotics, Multiagent systems, Internet of Things, Heriot-Watt University

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

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Posted in Human Robots