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July 28, 2022

A University of Washington team created a new tool that can design a 3D-printable passive gripper and calculate the best path to pick up an object. The researchers tested this system on a suite of 22 objects, which are shown here.University of Washington

At the beginning of the COVID-19 pandemic, car manufacturing companies such as Ford quickly shifted their production focus from automobiles to masks and ventilators.

To make this switch possible, these companies relied on people working on an assembly line. It would have been too challenging for a robot to make this transition because robots are tied to their usual tasks.

Theoretically, a robot could pick up almost anything if its grippers could be swapped out for each task. To keep costs down, these grippers could be passive, meaning grippers pick up objects without changing shape, similar to how the tongs on a forklift work.

A University of Washington team created a new tool that can design a 3D-printable passive gripper and calculate the best path to pick up an object. The team tested this system on a suite of 22 objects including a 3D-printed bunny, a doorstop-shaped wedge, a tennis ball and a drill. The designed grippers and paths were successful for 20 of the objects. Two of these were the wedge and a pyramid shape with a curved keyhole. Both shapes are challenging for multiple types of grippers to pick up.

The team will present these findings Aug. 11 at SIGGRAPH 2022.

We still produce most of our items with assembly lines, which are really great but also very rigid. The pandemic showed us that we need to have a way to easily repurpose these production lines, said senior author Adriana Schulz, a UW assistant professor in the Paul G. Allen School of Computer Science & Engineering. Our idea is to create custom tooling for these manufacturing lines. That gives us a very simple robot that can do one task with a specific gripper. And then when I change the task, I just replace the gripper.

Passive grippers cant adjust to fit the object theyre picking up, so traditionally, objects have been designed to match a specific gripper.

The most successful passive gripper in the world is the tongs on a forklift. But the trade-off is that forklift tongs only work well with specific shapes, such as pallets, which means anything you want to grip needs to be on a pallet, said co-author Jeffrey Lipton, UW assistant professor of mechanical engineering. Here were saying OK, we dont want to predefine the geometry of the passive gripper. Instead, we want to take the geometry of any object and design a gripper.

For any given object, there are many possibilities for what its gripper could look like. In addition, the grippers shape is linked to the path the robot arm takes to pick up the object. If designed incorrectly, a gripper could crash into the object en route to picking it up. To address this challenge, the researchers had a few key insights.

The points where the gripper makes contact with the object are essential for maintaining the objects stability in the grasp. We call this set of points the grasp configuration,' said lead author Milin Kodnongbua, who completed this research as a UW undergraduate student in the Allen School. Also, the gripper must contact the object at those given points, and the gripper must be a single solid object connecting the contact points to the robot arm. We can search for an insert trajectory that satisfies these requirements.

One of the objects was a blue 3D-printed bunny.University of Washington

When designing a new gripper and trajectory, the team starts by providing the computer with a 3D model of the object and its orientation in space how it would be presented on a conveyor belt, for example.

First our algorithm generates possible grasp configurations and ranks them based on stability and some other metrics, Kodnongbua said. Then it takes the best option and co-optimizes to find if an insert trajectory is possible. If it cannot find one, then it goes to the next grasp configuration on the list and tries to do the co-optimization again.

Once the computer has found a good match, it outputs two sets of instructions: one for a 3D printer to create the gripper and one with the trajectory for the robot arm once the gripper is printed and attached.

The team chose a variety of objects to test the power of the method, including some from a data set of objects that are the standard for testing a robots ability to do manipulation tasks.

We also designed objects that would be challenging for traditional grasping robots, such as objects with very shallow angles or objects with internal grasping where you have to pick them up with the insertion of a key, said co-author Ian Good, a UW doctoral student in the mechanical engineering department.

Play this video to see how a gripper can pick up one of the challenging shapes: a 3D-printed wedge. Credit: University of Washington

The researchers performed 10 test pickups with 22 shapes. For 16 shapes, all 10 pickups were successful. While most shapes had at least one successful pickup, two did not. These failures resulted from issues with the 3D models of the objects that were given to the computer. For one a bowl the model described the sides of the bowl as thinner than they were. For the other an object that looks like a cup with an egg-shaped handle the model did not have its correct orientation.

The algorithm developed the same gripping strategies for similarly shaped objects, even without any human intervention. The researchers hope that this means they will be able to create passive grippers that could pick up a class of objects, instead of having to have a unique gripper for each object.

One limitation of this method is that passive grippers cant be designed to pick up all objects. While its easier to pick up objects that vary in width or have protruding edges, objects with uniformly smooth surfaces, such as a water bottle or a box, are tough to grasp without any moving parts.

Still, the researchers were encouraged to see the algorithm do so well, especially with some of the more difficult shapes, such as a column with a keyhole at the top.

Play this video to see how a gripper can pick up the column with a keyhole at the top. Credit: University of Washington

The path that our algorithm came up with for that one is a rapid acceleration down to where it gets really close to the object. It looked like it was going to smash into the object, and I thought, Oh no. What if we didnt calibrate it right?' said Good. And then of course it gets incredibly close and then picks it up perfectly. It was this awe-inspiring moment, an extreme roller coaster of emotion.

Yu Lou, who completed this research as a masters student in the Allen School, is also a co-author on this paper. This research was funded by the National Science Foundation and a grant from the Murdock Charitable Trust. The team has also submitted a patent application: 63/339,284.

For more information, contact Kodnongbua at milink@cs.washington.edu, Lipton at jilipton@uw.edu, Schulz at adriana@cs.washington.edu, Good at iangood@uw.edu and Lou at louyu27@cs.washington.edu.

Grant number: EEC 2035717

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How to help assembly-line robots shift gears and pick up almost anything - University of Washington

I speak to women in the cybersecurity industry almost every single day, from our own security team, to prospective candidates, female CISOs, and security professionals at our customers' organizations. I ask them all some version of the same question: What do you wish every woman thinking about a career in cybersecurity knew?

After dozens if not hundreds of these conversations, there are three themes that I hear time and time again as the most important things to know for women when evaluating the cybersecurity profession.

Women still are underrepresented in software engineering and IT. And many times, cybersecurity gets lumped together with those, and with that comes the belief that it requires the same skills. And that's simply not the case. At the core, the job of cybersecurity teams is to assess, prioritize, and work to resolve risks; nothing in there requires a STEM background or understanding of software engineering.

Sure, these risks might related to code a developer wrote, or a cloud environment the IT team deployed, but reviewing alerts, assessing the impact to the business and the potential risk, and determining the appropriate course of action those arenot things that require a security professional to be a developer or to moonlight in IT. Computer science skills and backgrounds aren't a barrier to the cybersecurity profession we're a business function, not a technical one.

Over the last few years, we've seen more and more essential services, critical infrastructure, and leisure activities move online. This transformation has changed how we all work and live, and brought every aspect of modern business into the digital world, no matter what team you're on.

Software engineering teams creating new applications, hardware teams developing new mobile and virtual-reality devices, IT and DevOps teams building and maintaining cloud infrastructure, sales and marketing teams using all of these resources to track customer interactions and business metrics everyone has a piece of the digital pie.

If you're on a cybersecurity team, you're tasked with keeping all these teams safe, each and every day. But this isn't something you can do alone. You need help from all of them in order to deliver that protection. This can be anything from asking a team to change their process to support a better security outcome, to requesting a sudden change in priorities to address a critical risk.

Getting this help requires an investment in building relationships, finding the right communication styles for different teams or peers, and focusing on working together to help everyone be safer. Without investments in these skills, you'll find yourself siloed from the very people you're trying to protect every day.

Look, there's no denying cybersecurity is still a male dominated industry. In 2013, women were a mere 11% of the industry. But we're changing that every single day. Today, women are a quarter of the cybersecurity workforce. It took seven years to go from 11% to 20%, but only two years to go from there to 25%. We're closing the gender gap in cybersecurity faster than ever, across all aspects of the organization. And we're doing it together.

There are great organizations and programs out there that champion equality and diversity in cybersecurity, fromWomen in Cybersecurity (WiCyS) andWomen's Society of Cyberjutsu (WSC), to organizations like Cyersity that support all underrepresented groups in the industry. The SANS Institute has an immersion course for women career-changers and college students looking to learn more. There's a plethora of tools, groups, and resources to support you in your journey every step of the way. You won't be alone and every step you take helps us all.

Read more:

What Women Should Know Before Joining the Cybersecurity Industry - DARKReading

Extra time dimensions provide scientists with a new way to think about phases of matter for more stable qubits and robust quantum computers.

Quantum computers are built using qubits, the quantum analogs of classical bits, the function of which is based on two fundamental phenomena at the heart of quantum computing: quantum entanglement and the principle of superposition.

Superposition allows a qubit to exist as both a 0 and 1, unlike a bit, which can only take on one of these values, where entanglement leads to the subtle interactions a type of linking between qubits. Physically, qubits can be realized in a number of ways, for example, as photons with two different polarizations or ions trapped and controlled by electric field.

As a result, these machines are far superior to their conventional counterparts in solving specific types of problems, like analyzing data, simulating drug interactions, or optimizing supply chain logistics. But there is an obstacle to unlocking their full potential: maintaining stable qubits, which are crucial to running a functioning quantum computer, has proven quite the challenge.

These devices are extremely sensitive to external noise and even certain interactions between qubits, which forces them to fall out of their fragile quantum states. As a result, a fully functioning quantum computer has been very hard to build.

Even if you keep all the atoms under tight control, they can lose their quantumness by talking to their environment, heating up, or interacting with things in ways you didnt plan, said Philipp Dumitrescu of Flatiron Institutes Center for Computational Quantum Physics in New York City in an interview.

Dumitrescu is part of a new experimental study published in Nature, where he and his collaborators were able to better preserve the quantum states of qubits based on a previous theory put forth by a group of physicists, which included Demitrescu, Andrew Potter of the University of British Columbia in Vancouver, Romain Wasser of the University of Massachusetts at Amherst, and Ajesh Kumar of the University of Texas, Austin.

It is known that the interaction of qubits with a periodic electromagnetic pulse, similar to a radio wave, can make the quantum state of qubits more stable. By mathematically analyzing the interaction of qubits with different light pulses without restricting themselves to periodic shape, the theorists derived that a special shape to the pulse could make them more robust. According to the teams computations, the shape should be non-repeating, though ordered, such as the patterns of Penrose tiling in mathematics (feature image) and quasicrystals in physics.

With this quasi-periodic sequence, theres a complicated evolution that cancels out all the errors that live on the edge [or boundary of a system, which in the present case is one-dimensional with point-like boundaries], added Dumitrescu. Because of that, the edge stays quantum-mechanically coherent much, much longer than youd expect.

Their calculations showed that when ions at the ends of a chain of entangled qubits were radiated with the pulse, they retained their quantum properties much longer than without it. This effect was due to the fact that the mathematical description of this pair was as if they lived in one additional time dimension.

[Using an extra time dimension] is a completely different way of thinking about phases of matter, said Dumitrescu. Ive been working on these theory ideas for over five years and seeing them come actually to be realized in experiments is exciting.

To test this prediction, a group of experimentalists led by Brian Neyenhuis of Honeywell Quantum Solutions used Honeywells H1 quantum computer based on ten ytterbium ions.

They shined two laser pulse sequences at the qubits: the first sequence was periodic and the second, the one proposed by the theorists. In the periodic case, the edge qubits preserved the necessary entangled quantum state for around 1.5 seconds, which is very impressive for a quantum computer. But with the quasi-periodic pattern, the qubits stayed in their quantum states throughout the entire experiment, which lasted about 5.5 seconds.

This result demonstrates that the newly discovered qubit state can serve as a more solid foundation for quantum computing. However, researchers still need to understand how to incorporate their discovery into the real quantum computer algorithms.

Such an impressive result has been achieved for a one-dimensional system, but theorists predicted that higher-dimensional quantum systems could be even more error-resilient. The authors of the present study hope that their work will be an important step towards the practical realization of these theoretical studies.

Reference: Philipp T. Dumitrescu, et al., Dynamical topological phase realized in a trapped-ion quantum simulator, Nature (2022). DOI: 10.1038/s41586-022-04853-4

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Quantum bits that exist in two time dimensions - Advanced Science News