Tag Archives: operation

#435634 Robot Made of Clay Can Sculpt Its Own ...

Posted on September 14, 2019 by Android

We’re very familiar with a wide variety of transforming robots—whether for submarines or drones, transformation is a way of making a single robot adaptable to different environments or tasks. Usually, these robots are restricted to a discrete number of configurations—perhaps two or three different forms—because of the constraints imposed by the rigid structures that robots are typically made of.

Soft robotics has the potential to change all this, with robots that don’t have fixed forms but instead can transform themselves into whatever shape will enable them to do what they need to do. At ICRA in Montreal earlier this year, researchers from Yale University demonstrated a creative approach toward a transforming robot powered by string and air, with a body made primarily out of clay.

Photo: Evan Ackerman

The robot is actuated by two different kinds of “skin,” one layered on top of another. There’s a locomotion skin, made of a pattern of pneumatic bladders that can roll the robot forward or backward when the bladders are inflated sequentially. On top of that is the morphing skin, which is cable-driven, and can sculpt the underlying material into a variety of shapes, including spheres, cylinders, and dumbbells. The robot itself consists of both of those skins wrapped around a chunk of clay, with the actuators driven by offboard power and control. Here it is in action:

The Yale researchers have been experimenting with morphing robots that use foams and tensegrity structures for their bodies, but that stuff provides a “restoring force,” springing back into its original shape once the actuation stops. Clay is different because it holds whatever shape it’s formed into, making the robot more energy efficient. And if the dumbbell shape stops being useful, the morphing layer can just squeeze it back into a cylinder or a sphere.

While this robot, and the sample transformation shown in the video, are relatively simplistic, the researchers suggest some ways in which a more complex version could be used in the future:

Photo: IEEE Xplore

This robot’s morphing skin sculpts its clay body into different shapes.

Applications where morphing and locomotion might serve as complementary functions are abundant. For the example skins presented in this work, a search-and-rescue operation could use the clay as a medium to hold a payload such as sensors or transmitters. More broadly, applications include resource-limited conditions where supply chains for materiel are sparse. For example, the morphing sequence shown in Fig. 4 [above] could be used to transform from a rolling sphere to a pseudo-jointed robotic arm. With such a morphing system, it would be possible to robotically morph matter into different forms to perform different functions.

Read this article for free on IEEE Xplore until 5 September 2019

Morphing Robots Using Robotic Skins That Sculpt Clay, by Dylan S. Shah, Michelle C. Yuen, Liana G. Tilton, Ellen J. Yang, and Rebecca Kramer-Bottiglio from Yale University, was presented at ICRA 2019 in Montreal.

[ Yale Faboratory ]

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#435621 ANYbotics Introduces Sleek New ANYmal C ...

Posted on September 13, 2019 by Android

Quadrupedal robots are making significant advances lately, and just in the past few months we’ve seen Boston Dynamics’ Spot hauling a truck, IIT’s HyQReal pulling a plane, MIT’s MiniCheetah doing backflips, Unitree Robotics’ Laikago towing a van, and Ghost Robotics’ Vision 60 exploring a mine. Robot makers are betting that their four-legged machines will prove useful in a variety of applications in construction, security, delivery, and even at home.

ANYbotics has been working on such applications for years, testing out their ANYmal robot in places where humans typically don’t want to go (like offshore platforms) as well as places where humans really don’t want to go (like sewers), and they have a better idea than most companies what can make quadruped robots successful.

This week, ANYbotics is announcing a completely new quadruped platform, ANYmal C, a major upgrade from the really quite research-y ANYmal B. The new quadruped has been optimized for ruggedness and reliability in industrial environments, with a streamlined body painted a color that lets you know it means business.

ANYmal C’s physical specs are pretty impressive for a production quadruped. It can move at 1 meter per second, manage 20-degree slopes and 45-degree stairs, cross 25-centimeter gaps, and squeeze through passages just 60 centimeters wide. It’s packed with cameras and 3D sensors, including a lidar for 3D mapping and simultaneous localization and mapping (SLAM). All these sensors (along with the vast volume of gait research that’s been done with ANYmal) make this one of the most reliably autonomous quadrupeds out there, with real-time motion planning and obstacle avoidance.

Image: ANYbotics

ANYmal can autonomously attach itself to a cone-shaped docking station to recharge.

ANYmal C is also one of the ruggedest legged robots in existence. The 50-kilogram robot is IP67 rated, meaning that it’s completely impervious to dust and can withstand being submerged in a meter of water for an hour. If it’s submerged for longer than that, you’re absolutely doing something wrong. The robot will run for over 2 hours on battery power, and if that’s not enough endurance, don’t worry, because ANYmal can autonomously impale itself on a weird cone-shaped docking station to recharge.

Photo: ANYbotics

ANYmal C’s sensor payload includes cameras and a lidar for 3D mapping and SLAM.

As far as what ANYmal C is designed to actually do, it’s mostly remote inspection tasks where you need to move around through a relatively complex environment, but where for whatever reason you’d be better off not sending a human. ANYmal C has a sensor payload that gives it lots of visual options, like thermal imaging, and with the ability to handle a 10-kilogram payload, the robot can be adapted to many different environments.

Over the next few months, we’re hoping to see more examples of ANYmal C being deployed to do useful stuff in real-world environments, but for now, we do have a bit more detail from ANYbotics CTO Christian Gehring.

IEEE Spectrum: Can you tell us about the development process for ANYmal C?

Christian Gehring: We tested the previous generation of ANYmal (B) in a broad range of environments over the last few years and gained a lot of insights. Based on our learnings, it became clear that we would have to re-design the robot to meet the requirements of industrial customers in terms of safety, quality, reliability, and lifetime. There were different prototype stages both for the new drives and for single robot assemblies. Apart from electrical tests, we thoroughly tested the thermal control and ingress protection of various subsystems like the depth cameras and actuators.

What can ANYmal C do that the previous version of ANYmal can’t?

ANYmal C was redesigned with a focus on performance increase regarding actuation (new drives), computational power (new hexacore Intel i7 PCs), locomotion and navigation skills, and autonomy (new depth cameras). The new robot additionally features a docking system for autonomous recharging and an inspection payload as an option. The design of ANYmal C is far more integrated than its predecessor, which increases both performance and reliability.

How much of ANYmal C’s development and design was driven by your experience with commercial or industry customers?

Tests (such as the offshore installation with TenneT) and discussions with industry customers were important to get the necessary design input in terms of performance, safety, quality, reliability, and lifetime. Most customers ask for very similar inspection tasks that can be performed with our standard inspection payload and the required software packages. Some are looking for a robot that can also solve some simple manipulation tasks like pushing a button. Overall, most use cases customers have in mind are realistic and achievable, but some are really tough for the robot, like climbing 50° stairs in hot environments of 50°C.

Can you describe how much autonomy you expect ANYmal C to have in industrial or commercial operations?

ANYmal C is primarily developed to perform autonomous routine inspections in industrial environments. This autonomy especially adds value for operations that are difficult to access, as human operation is extremely costly. The robot can naturally also be operated via a remote control and we are working on long-distance remote operation as well.

Do you expect that researchers will be interested in ANYmal C? What research applications could it be useful for?

ANYmal C has been designed to also address the needs of the research community. The robot comes with two powerful hexacore Intel i7 computers and can additionally be equipped with an NVIDIA Jetson Xavier graphics card for learning-based applications. Payload interfaces enable users to easily install and test new sensors. By joining our established ANYmal Research community, researchers get access to simulation tools and software APIs, which boosts their research in various areas like control, machine learning, and navigation.

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#435597 Water Jet Powered Drone Takes Off With ...

Posted on September 12, 2019 by Android

At ICRA 2015, the Aerial Robotics Lab at the Imperial College London presented a concept for a multimodal flying swimming robot called AquaMAV. The really difficult thing about a flying and swimming robot isn’t so much the transition from the first to the second, since you can manage that even if your robot is completely dead (thanks to gravity), but rather the other way: going from water to air, ideally in a stable and repetitive way. The AquaMAV concept solved this by basically just applying as much concentrated power as possible to the problem, using a jet thruster to hurl the robot out of the water with quite a bit of velocity to spare.

In a paper appearing in Science Robotics this week, the roboticists behind AquaMAV present a fully operational robot that uses a solid-fuel powered chemical reaction to generate an explosion that powers the robot into the air.

The 2015 version of AquaMAV, which was mostly just some very vintage-looking computer renderings and a little bit of hardware, used a small cylinder of CO2 to power its water jet thruster. This worked pretty well, but the mass and complexity of the storage and release mechanism for the compressed gas wasn’t all that practical for a flying robot designed for long-term autonomy. It’s a familiar challenge, especially for pneumatically powered soft robots—how do you efficiently generate gas on-demand, especially if you need a lot of pressure all at once?

An explosion propels the drone out of the water
There’s one obvious way of generating large amounts of pressurized gas all at once, and that’s explosions. We’ve seen robots use explosive thrust for mobility before, at a variety of scales, and it’s very effective as long as you can both properly harness the explosion and generate the fuel with a minimum of fuss, and this latest version of AquaMAV manages to do both:

The water jet coming out the back of this robot aircraft is being propelled by a gas explosion. The gas comes from the reaction between a little bit of calcium carbide powder stored inside the robot, and water. Water is mixed with the powder one drop at a time, producing acetylene gas, which gets piped into a combustion chamber along with air and water. When ignited, the acetylene air mixture explodes, forcing the water out of the combustion chamber and providing up to 51 N of thrust, which is enough to launch the 160-gram robot 26 meters up and over the water at 11 m/s. It takes just 50 mg of calcium carbide (mixed with 3 drops of water) to generate enough acetylene for each explosion, and both air and water are of course readily available. With 0.2 g of calcium carbide powder on board, the robot has enough fuel for multiple jumps, and the jump is powerful enough that the robot can get airborne even under fairly aggressive sea conditions.

Image: Science Robotics

The robot can transition from a floating state to an airborne jetting phase and back to floating (A). A 3D model render of the underside of the robot (B) shows the electronics capsule. The capsule contains the fuel tank (C), where calcium carbide reacts with air and water to propel the vehicle.

Next step: getting the robot to fly autonomously
Providing adequate thrust is just one problem that needs to be solved when attempting to conquer the water-air transition with a fixed-wing robot. The overall design of the robot itself is a challenge as well, because the optimal design and balance for the robot is quite different in each phase of operation, as the paper describes:

For the vehicle to fly in a stable manner during the jetting phase, the center of mass must be a significant distance in front of the center of pressure of the vehicle. However, to maintain a stable floating position on the water surface and the desired angle during jetting, the center of mass must be located behind the center of buoyancy. For the gliding phase, a fine balance between the center of mass and the center of pressure must be struck to achieve static longitudinal flight stability passively. During gliding, the center of mass should be slightly forward from the wing’s center of pressure.

The current version is mostly optimized for the jetting phase of flight, and doesn’t have any active flight control surfaces yet, but the researchers are optimistic that if they added some they’d have no problem getting the robot to fly autonomously. It’s just a glider at the moment, but a low-power propeller is the obvious step after that, and to get really fancy, a switchable gearbox could enable efficient movement on water as well as in the air. Long-term, the idea is that robots like these would be useful for tasks like autonomous water sampling over large areas, but I’d personally be satisfied with a remote controlled version that I could take to the beach.

“Consecutive aquatic jump-gliding with water-reactive fuel,” by R. Zufferey, A. Ortega Ancel, A. Farinha, R. Siddall, S. F. Armanini, M. Nasr, R. V. Brahmal, G. Kennedy, and M. Kovac from Imperial College in London, is published in the current issue of Science Robotics. Continue reading →

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#435593 AI at the Speed of Light

Posted on September 11, 2019 by Android

Neural networks shine for solving tough problems such as facial and voice recognition, but conventional electronic versions are limited in speed and hungry for power. In theory, optics could beat digital electronic computers in the matrix calculations used in neural networks. However, optics had been limited by their inability to do some complex calculations that had required electronics. Now new experiments show that all-optical neural networks can tackle those problems.

The key attraction of neural networks is their massive interconnections among processors, comparable to the complex interconnections among neurons in the brain. This lets them perform many operations simultaneously, like the human brain does when looking at faces or listening to speech, making them more efficient for facial and voice recognition than traditional electronic computers that execute one instruction at a time.

Today's electronic neural networks have reached eight million neurons, but their future use in artificial intelligence may be limited by their high power usage and limited parallelism in connections. Optical connections through lenses are inherently parallel. The lens in your eye simultaneously focuses light from across your field of view onto the retina in the back of your eye, where an array of light-detecting nerve cells detects the light. Each cell then relays the signal it receives to neurons in the brain that process the visual signals to show us an image.

Glass lenses process optical signals by focusing light, which performs a complex mathematical operation called a Fourier transform that preserves the information in the original scene but rearranges is completely. One use of Fourier transforms is converting time variations in signal intensity into a plot of the frequencies present in the signal. The military used this trick in the 1950s to convert raw radar return signals recorded by an aircraft in flight into a three-dimensional image of the landscape viewed by the plane. Today that conversion is done electronically, but the vacuum-tube computers of the 1950s were not up to the task.

Development of neural networks for artificial intelligence started with electronics, but their AI applications have been limited by their slow processing and need for extensive computing resources. Some researchers have developed hybrid neural networks, in which optics perform simple linear operations, but electronics perform more complex nonlinear calculations. Now two groups have demonstrated simple all-optical neural networks that do all processing with light.

In May, Wolfram Pernice of the Institute of Physics at the University of Münster in Germany and colleagues reported testing an all-optical “neuron” in which signals change target materials between liquid and solid states, an effect that has been used for optical data storage. They demonstrated nonlinear processing, and produced output pulses like those from organic neurons. They then produced an integrated photonic circuit that incorporated four optical neurons operating at different wavelengths, each of which connected to 15 optical synapses. The photonic circuit contained more than 140 components and could recognize simple optical patterns. The group wrote that their device is scalable, and that the technology promises “access to the high speed and high bandwidth inherent to optical systems, thus enabling the direct processing of optical telecommunication and visual data.”

Now a group at the Hong Kong University of Science and Technology reports in Optica that they have made an all-optical neural network based on a different process, electromagnetically induced transparency, in which incident light affects how atoms shift between quantum-mechanical energy levels. The process is nonlinear and can be triggered by very weak light signals, says Shengwang Du, a physics professor and coauthor of the paper.

In their demonstration, they illuminated rubidium-85 atoms cooled by lasers to about 10 microKelvin (10 microdegrees above absolute zero). Although the technique may seem unusually complex, Du said the system was the most accessible one in the lab that could produce the desired effects. “As a pure quantum atomic system [it] is ideal for this proof-of-principle experiment,” he says.

Next, they plan to scale up the demonstration using a hot atomic vapor center, which is less expensive, does not require time-consuming preparation of cold atoms, and can be integrated with photonic chips. Du says the major challenges are reducing cost of the nonlinear processing medium and increasing the scale of the all-optical neural network for more complex tasks.

“Their demonstration seems valid,” says Volker Sorger, an electrical engineer at George Washington University in Washington who was not involved in either demonstration. He says the all-optical approach is attractive because it offers very high parallelism, but the update rate is limited to about 100 hertz because of the liquid crystals used in their test, and he is not completely convinced their approach can be scaled error-free. Continue reading →

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#435436 Undeclared Wars in Cyberspace Are ...

Posted on August 1, 2019 by Android

The US is at war. That’s probably not exactly news, as the country has been engaged in one type of conflict or another for most of its history. The last time we officially declared war was after Japan bombed Pearl Harbor in December 1941.

Our biggest undeclared war today is not being fought by drones in the mountains of Afghanistan or even through the less-lethal barrage of threats over the nuclear programs in North Korea and Iran. In this particular war, it is the US that is under attack and on the defensive.

This is cyberwarfare.

The definition of what constitutes a cyber attack is a broad one, according to Greg White, executive director of the Center for Infrastructure Assurance and Security (CIAS) at The University of Texas at San Antonio (UTSA).

At the level of nation-state attacks, cyberwarfare could involve “attacking systems during peacetime—such as our power grid or election systems—or it could be during war time in which case the attacks may be designed to cause destruction, damage, deception, or death,” he told Singularity Hub.

For the US, the Pearl Harbor of cyberwarfare occurred during 2016 with the Russian interference in the presidential election. However, according to White, an Air Force veteran who has been involved in computer and network security since 1986, the history of cyber war can be traced back much further, to at least the first Gulf War of the early 1990s.

“We started experimenting with cyber attacks during the first Gulf War, so this has been going on a long time,” he said. “Espionage was the prime reason before that. After the war, the possibility of expanding the types of targets utilized expanded somewhat. What is really interesting is the use of social media and things like websites for [psychological operation] purposes during a conflict.”

The 2008 conflict between Russia and the Republic of Georgia is often cited as a cyberwarfare case study due to the large scale and overt nature of the cyber attacks. Russian hackers managed to bring down more than 50 news, government, and financial websites through denial-of-service attacks. In addition, about 35 percent of Georgia’s internet networks suffered decreased functionality during the attacks, coinciding with the Russian invasion of South Ossetia.

The cyberwar also offers lessons for today on Russia’s approach to cyberspace as a tool for “holistic psychological manipulation and information warfare,” according to a 2018 report called Understanding Cyberwarfare from the Modern War Institute at West Point.

US Fights Back
News in recent years has highlighted how Russian hackers have attacked various US government entities and critical infrastructure such as energy and manufacturing. In particular, a shadowy group known as Unit 26165 within the country’s military intelligence directorate is believed to be behind the 2016 US election interference campaign.

However, the US hasn’t been standing idly by. Since at least 2012, the US has put reconnaissance probes into the control systems of the Russian electric grid, The New York Times reported. More recently, we learned that the US military has gone on the offensive, putting “crippling malware” inside the Russian power grid as the U.S. Cyber Command flexes its online muscles thanks to new authority granted to it last year.

“Access to the power grid that is obtained now could be used to shut something important down in the future when we are in a war,” White noted. “Espionage is part of the whole program. It is important to remember that cyber has just provided a new domain in which to conduct the types of activities we have been doing in the real world for years.”

The US is also beginning to pour more money into cybersecurity. The 2020 fiscal budget calls for spending $17.4 billion throughout the government on cyber-related activities, with the Department of Defense (DoD) alone earmarked for $9.6 billion.

Despite the growing emphasis on cybersecurity in the US and around the world, the demand for skilled security professionals is well outpacing the supply, with a projected shortfall of nearly three million open or unfilled positions according to the non-profit IT security organization (ISC)².

UTSA is rare among US educational institutions in that security courses and research are being conducted across three different colleges, according to White. About 10 percent of the school’s 30,000-plus students are enrolled in a cyber-related program, he added, and UTSA is one of only 21 schools that has received the Cyber Operations Center of Excellence designation from the National Security Agency.

“This track in the computer science program is specifically designed to prepare students for the type of jobs they might be involved in if they went to work for the DoD,” White said.

However, White is extremely doubtful there will ever be enough cyber security professionals to meet demand. “I’ve been preaching that we’ve got to worry about cybersecurity in the workforce, not just the cybersecurity workforce, not just cybersecurity professionals. Everybody has a responsibility for cybersecurity.”

Artificial Intelligence in Cybersecurity
Indeed, humans are often seen as the weak link in cybersecurity. That point was driven home at a cybersecurity roundtable discussion during this year’s Brainstorm Tech conference in Aspen, Colorado.

Participant Dorian Daley, general counsel at Oracle, said insider threats are at the top of the list when it comes to cybersecurity. “Sadly, I think some of the biggest challenges are people, and I mean that in a number of ways. A lot of the breaches really come from insiders. So the more that you can automate things and you can eliminate human malicious conduct, the better.”

White noted that automation is already the norm in cybersecurity. “Humans can’t react as fast as systems can launch attacks, so we need to rely on automated defenses as well,” he said. “This doesn’t mean that humans are not in the loop, but much of what is done these days is ‘scripted’.”

The use of artificial intelligence, machine learning, and other advanced automation techniques have been part of the cybersecurity conversation for quite some time, according to White, such as pattern analysis to look for specific behaviors that might indicate an attack is underway.

“What we are seeing quite a bit of today falls under the heading of big data and data analytics,” he explained.

But there are signs that AI is going off-script when it comes to cyber attacks. In the hands of threat groups, AI applications could lead to an increase in the number of cyberattacks, wrote Michelle Cantos, a strategic intelligence analyst at cybersecurity firm FireEye.

“Current AI technology used by businesses to analyze consumer behavior and find new customer bases can be appropriated to help attackers find better targets,” she said. “Adversaries can use AI to analyze datasets and generate recommendations for high-value targets they think the adversary should hit.”

In fact, security researchers have already demonstrated how a machine learning system could be used for malicious purposes. The Social Network Automated Phishing with Reconnaissance system, or SNAP_R, generated more than four times as many spear-phishing tweets on Twitter than a human—and was just as successful at targeting victims in order to steal sensitive information.

Cyber war is upon us. And like the current war on terrorism, there are many battlefields from which the enemy can attack and then disappear. While total victory is highly unlikely in the traditional sense, innovations through AI and other technologies can help keep the lights on against the next cyber attack.

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