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“Cover, bring to a boil, then reduce heat. Simmer for 20 minutes.” These directions seem simple enough, and yet I have messed up many, many pots of rice over the years. My sympathies to anyone who’s ever had to boil rice on a stovetop, cook it in a clay pot over a kerosene or charcoal burner, or prepare it in a cast-iron cauldron. All hail the 1955 invention of the automatic rice cooker!

How the automatic rice cooker was invented

It isn’t often that housewives get credit in the annals of invention, but in the story of the automatic rice cooker, a woman takes center stage. That happened only after the first attempts at electrifying rice cooking, starting in the 1920s, turned out to be utter failures. Matsushita, Mitsubishi, and Sony all experimented with variations of placing electric heating coils inside wooden tubs or aluminum pots, but none of these cookers automatically switched off when the rice was done. The human cook—almost always a wife or daughter—still had to pay attention to avoid burning the rice. These electric rice cookers didn’t save any real time or effort, and they sold poorly.

But Shogo Yamada, the energetic development manager of the electric appliance division for Toshiba, became convinced that his company could do better. In post–World War II Japan, he was demonstrating and selling electric washing machines all over the country. When he took a break from his sales pitch and actually talked to women about their daily household labors, he discovered that cooking rice—not laundry—was their most challenging chore. Rice was a mainstay of the Japanese diet, and women had to prepare it up to three times a day. It took hours of work, starting with getting up by 5:00 am to fan the flames of a kamado, a traditional earthenware stove fueled by charcoal or wood on which the rice pot was heated. The inability to properly mind the flame could earn a woman the label of “failed housewife.”

In 1951, Yamada became the cheerleader of the rice cooker within Toshiba, which was understandably skittish given the past failures of other companies. To develop the product, he turned to Yoshitada Minami, the manager of a small family factory that produced electric water heaters for Toshiba. The water-heater business wasn’t great, and the factory was on the brink of bankruptcy.

How Sources Influence the Telling of History

As someone who does a lot of research online, I often come across websites that tell very interesting histories, but without any citations. It takes only a little bit of digging before I find entire passages copied and pasted from one site to another, and so I spend a tremendous amount of time trying to track down the original source. Accounts of popular consumer products, such as the rice cooker, are particularly prone to this problem. That’s not to say that popular accounts are necessarily wrong; plus they are often much more engaging than boring academic pieces. This is just me offering a note of caution because every story offers a different perspective depending on its sources.

For example, many popular blogs sing the praises of Fumiko Minami and her tireless contributions to the development of the rice maker. But in my research, I found no mention of Minami before Helen Macnaughtan’s 2012 book chapter, “Building up Steam as Consumers: Women, Rice Cookers and the Consumption of Everyday Household Goods in Japan,” which itself was based on episode 42 of the Project X: Challengers documentary series that was produced by NHK and aired in 2002.

If instead I had relied solely on the description of the rice cooker’s early development provided by the Toshiba Science Museum (here’s an archived page from 2007), this month’s column would have offered a detailed technical description of how uncooked rice has a crystalline structure, but as it cooks, it becomes a gelatinized starch. The museum’s website notes that few engineers had ever considered the nature of cooking rice before the rice-cooker project, and it refers simply to the “project team” that discovered the process. There’s no mention of Fumiko.

Both stories are factually correct, but they emphasize different details. Sometimes it’s worth asking who is part of the “project team” because the answer might surprise you. —A.M.

Although Minami understood the basic technical principles for an electric rice cooker, he didn’t know or appreciate the finer details of preparing perfect rice. And so Minami turned to his wife, Fumiko.

Fumiko, the mother of six children, spent five years researching and testing to document the ideal recipe. She continued to make rice three times a day, carefully measuring water-to-rice ratios, noting temperatures and timings, and prototyping rice-cooker designs. Conventional wisdom was that the heat source needed to be adjusted continuously to guarantee fluffy rice, but Fumiko found that heating the water and rice to a boil and then cooking for exactly 20 minutes produced consistently good results.

But how would an automatic rice cooker know when the 20 minutes was up? A suggestion came from Toshiba engineers. A working model based on a double boiler (a pot within a pot for indirect heating) used evaporation to mark time. While the rice cooked in the inset pot, a bimetallic switch measured the temperature in the external pot. Boiling water would hold at a constant 100 °C, but once it had evaporated, the temperature would soar. When the internal temperature of the double boiler surpassed 100 °C, the switch would bend and cut the circuit. One cup of boiling water in the external pot took 20 minutes to evaporate. The same basic principle is still used in modern cookers.

Yamada wanted to ensure that the rice cooker worked in all climates, so Fumiko tested various prototypes in extreme conditions: on her rooftop in cold winters and scorching summers and near steamy bathrooms to mimic high humidity. When Fumiko became ill from testing outside, her children pitched in to help. None of the aluminum and glass prototypes, it turned out, could maintain their internal temperature in cold weather. The final design drew inspiration from the Hokkaidō region, Japan’s northernmost prefecture. Yamada had seen insulated cooking pots there, so the Minami family tried covering the rice cooker with a triple-layered iron exterior. It worked.

How Toshiba sold its automatic rice cooker

Toshiba’s automatic rice cooker went on sale on 10 December 1955, but initially, sales were slow. It didn’t help that the rice cooker was priced at 3,200 yen, about a third of the average Japanese monthly salary. It took some salesmanship to convince women they needed the new appliance. This was Yamada’s time to shine. He demonstrated using the rice cooker to prepare takikomi gohan, a rice dish seasoned with dashi, soy sauce, and a selection of meats and vegetables. When the dish was cooked in a traditional kamado, the soy sauce often burned, making the rather simple dish difficult to master. Women who saw Yamada’s demo were impressed with the ease offered by the rice cooker.

Another clever sales technique was to get electricity companies to serve as Toshiba distributors. At the time, Japan was facing a national power surplus stemming from the widespread replacement of carbon-filament lightbulbs with more efficient tungsten ones. The energy savings were so remarkable that operations at half of the country’s power plants had to be curtailed. But with utilities distributing Toshiba rice cookers, increased demand for electricity was baked in.

Within a year, Toshiba was selling more than 200,000 rice cookers a month. Many of them came from the Minamis’ factory, which was rescued from near-bankruptcy in the process.

How the automatic rice cooker conquered the world

From there, the story becomes an international one with complex localization issues. Japanese sushi rice is not the same as Thai sticky rice which is not the same as Persian tahdig, Indian basmati, Italian risotto, or Spanish paella. You see where I’m going with this. Every culture that has a unique rice dish almost always uses its own regional rice with its own preparation preferences. And so countries wanted their own type of automatic electric rice cooker (although some rejected automation in favor of traditional cooking methods).

Yoshiko Nakano, a professor at the University of Hong Kong, wrote a book in 2009 about the localized/globalized nature of rice cookers. Where There Are Asians, There Are Rice Cookers traces the popularization of the rice cooker from Japan to China and then the world by way of Hong Kong. One of the key differences between the Japanese and Chinese rice cooker is that the latter has a glass lid, which Chinese cooks demanded so they could see when to add sausage. More innovation and diversification followed. Modern rice cookers have settings to give Iranians crispy rice at the bottom of the pot, one to let Thai customers cook noodles, one for perfect rice porridge, and one for steel-cut oats.

My friend Hyungsub Choi, in his 2022 article “Before Localization: The Story of the Electric Rice Cooker in South Korea,” pushes back a bit on Nakano’s argument that countries were insistent on tailoring cookers to their tastes. From 1965, when the first domestic rice cooker appeared in South Korea, to the early 1990s, Korean manufacturers engaged in “conscious copying,” Choi argues. That is, they didn’t bother with either innovation or adaptation. As a result, most Koreans had to put up with inferior domestic models. Even after the Korean government made it a national goal to build a better rice cooker, manufacturers failed to deliver one, perhaps because none of the engineers involved knew how to cook rice. It’s a good reminder that the history of technology is not always the story of innovation and progress.

Eventually, the Asian diaspora brought the rice cooker to all parts of the globe, including South Carolina, where I now live and which coincidentally has a long history of rice cultivation. I bought my first rice cooker on a whim, but not for its rice-cooking ability. I was intrigued by the yogurt-making function. Similar to rice, yogurt requires a constant temperature over a specific length of time. Although successful, my yogurt experiment was fleeting—store-bought was just too convenient. But the rice cooking blew my mind. Perfect rice. Every. Single. Time. I am never going back to overflowing pots of starchy water.

Part of a continuing series looking at historical artifacts that embrace the boundless potential of technology.

An abridged version of this article appears in the November 2024 print issue as “The Automatic Rice Cooker’s Unlikely Inventor.”

References

Helen Macnaughtan’s 2012 book chapter, “Building up Steam as Consumers: Women, Rice Cookers and the Consumption of Everyday Household Goods in Japan,” was a great resource in understanding the development of the Toshiba ER-4. The chapter appeared in The Historical Consumer: Consumption and Everyday Life in Japan, 1850-2000, edited by Penelope Francks and Janet Hunter (Palgrave Macmillan).

Yoshiko Nakano’s book Where There are Asians, There are Rice Cookers (Hong Kong University Press, 2009) takes the story much further with her focus on the National (Panasonic) rice cooker and its adaptation and adoption around the world.

The Toshiba Science Museum, in Kawasaki, Japan, where we sourced our main image of the original ER-4, closed to the public in June. I do not know what the future holds for its collections, but luckily some of its Web pages have been archived to continue to help researchers like me.

As the philanthropic partner of IEEE, the IEEE Foundation expands the organization’s charitable body of work by inspiring philanthropic engagement that ignites a donor’s innermost interests and values.

One way the Foundation does so is by partnering with IEEE units to create memorial funds, which pay tribute to members, family, friends, teachers, professors, students, and others. This type of giving honors someone special while also supporting future generations of engineers and celebrating innovation.

Below are three recently created memorial funds that not only have made an impact on their beneficiaries and perpetuated the legacy of the namesake but also have a deep meaning for those who launched them.

EPICS in IEEE Fischer Mertel Community of Projects

The EPICS in IEEE Fischer Mertel Community of Projects was established to support projects “designed to inspire multidisciplinary teams of engineering students to collaborate and engineer solutions to address local community needs.”

The fund was created by the children of Joe Fischer and Herb Mertel to honor their fathers’ passion for mentoring students. Longtime IEEE members, Fischer and Mertel were active with the IEEE Electromagnetic Compatibility Society. Fischer was the society’s 1972 president and served on its board of directors for six years. Mertel served on the society’s board from 1979 to 1983 and again from 1989 to 1993.

“The EPICS in IEEE Fischer Mertel Community of Projects was established to inspire and support outstanding engineering ideas and efforts that help communities worldwide,” says Tina Mertel, Herb’s daughter. “Joe Fischer and my father had a lifelong friendship and excelled as engineering leaders and founders of their respective companies [Fischer Custom Communications and EMACO]. I think that my father would have been proud to know that their friendship and work are being honored in this way.”

The nine projects supported thus far have the potential to impact more than 104,000 people because of the work and collaboration of 190 students worldwide. The projects funded are intended to represent at least two of the EPICS in IEEE’s focus categories: education and outreach; human services; environmental; and access and abilities.

Here are a few of the projects:

• The Engineering Outreach at San Diego K–12 Schools project aims to bridge the city’s STEM education gap by sending IEEE members to schools to teach project-based lessons in mechanical, aerospace, electrical and computer engineering, as well as computer science. The project is led by the IEEE–Eta Kappa Nu honor society’s Kappa Psi chapter at the University of California San Diego and the San Diego Unified School District.
• Students from the Sahrdaya College of Engineering and Technology student branch in Kodakara, India, are developing an exoskeleton for nurses to support their lumbar spine region.
• Volunteers from the IEEE Uganda Section and local engineering students are designing and fabricating a stationary bicycle to act as a generator, providing power to families living in underserved communities. The goal of the project is to reduce air pollution caused by generators and supply reliable, affordable power to people in need.
• The IEEE Colombian Caribbean Section’s Increasing Inclusion of Visually Impaired People with a Mobile Application for English Learning project aims to ensure visually impaired students can learn to read, write, and speak English alongside their peers. The section’s members are developing a mobile app to help accomplish their goal.

IEEE AESS Michael C. Wicks Radar Student Travel Grant

The IEEE Michael C. Wicks Radar Student Travel Grant was established by IEEE Fellow Michael Wicks prior to his death in 2022. The grant provides travel support for graduate students who are the primary authors on a paper being presented at the annual IEEE Radar Conference. Wicks was an electronics engineer and a radio industry leader who was known for developing knowledge-based space-time adaptive processing. He believed in investing in the next generation and he wanted to provide an opportunity for that to happen.Ten graduate students have been awarded the Wicks grant to date. This year two students from Region 8 (Africa, Europe, Middle East) and two students from Region 10 (Asia and Pacific) were able to travel to Denver to attend the IEEE Radar Conference and present their research. The papers they presented are “Target Shape Reconstruction From Multi-Perspective Shadows in Drone-Borne SAR Systems” and “Design of Convolutional Neural Networks for Classification of Ships from ISAR Images.”

Life Fellow Fumio Koyama and IEEE Fellow Constance J. Chang-Hasnain proudly display their IEEE Nick Holonyak, Jr. Medal for Semiconductor Optoelectronic Technologies at this year’s IEEE Honors Ceremony. They are accompanied by IEEE President-Elect Kathleen Kramer and IEEE President Tom Coughlin.Robb Cohen

IEEE Nick Holonyak Jr. Medal for Semiconductor Optoelectronic Technologies

The IEEE Nick Holonyak Jr. Medal for Semiconductor Optoelectronic Technologies was created with a memorial fund supported by some of Holonyak’s former graduate students to honor his work as a professor and mentor. Presented on behalf of the IEEE Board of Directors, the medal recognizes outstanding contributions to semiconductor optoelectronic devices and systems including high-energy-efficiency semiconductor devices and electronics.

Holonyak was a prolific inventor and longtime professor of electrical engineering and physics. In 1962, while working as a scientist at General Electric’s Advanced Semiconductor Laboratory in Syracuse, N.Y., he invented the first practical visible-spectrum LED and laser diode. His innovations are the basis of the devices now used in high-efficiency light bulbs and laser diodes. He left GE in 1963 to join the University of Illinois Urbana-Champaign as a professor of electrical engineering and physics at the invitation of John Bardeen, his Ph.D. advisor and a two-time Nobel Prize winner in physics. Holonyak retired from UIUC in 2013 but continued research collaborations at the university with young faculty members.

“In addition to his remarkable technical contributions, he was an excellent teacher and mentor to graduate students and young electrical engineers,” says Russell Dupuis, one of his doctoral students. “The impact of his innovations has improved the lives of most people on the earth, and this impact will only increase with time. It was my great honor to be one of his students and to help create this important IEEE medal to ensure that his work will be remembered in the future.”

The award was presented for the first time at this year’s IEEE Honors Ceremony, in Boston, to IEEE Fellow Constance Chang-Hasnain and Life Fellow Fumio Koyama for “pioneering contributions to vertical cavity surface-emitting laser (VCSEL) and VCSEL-based photonics for optical communications and sensing.”

Establishing a memorial fund through the IEEE Foundation is a gratifying way to recognize someone who has touched your life while also advancing technology for humanity. If you are interested in learning more about memorial and tribute funds, reach out to the IEEE Foundation team: donate@ieee.org.

Every invention begins with a problem—and the creative act of seeing a problem where others might just see unchangeable reality. For one 5-year-old, the problem was simple: She liked to have her tummy rubbed as she fell asleep. But her mom, exhausted from working two jobs, often fell asleep herself while putting her daughter to bed. “So [the girl] invented a teddy bear that would rub her belly for her,” explains Stephanie Couch, executive director of the Lemelson MIT Program. Its mission is to nurture the next generation of inventors and entrepreneurs.

Anyone can learn to be an inventor, Couch says, given the right resources and encouragement. “Invention doesn’t come from some innate genius, it’s not something that only really special people get to do,” she says. Her program creates invention-themed curricula for U.S. classrooms, ranging from kindergarten to community college.

We’re biased, but we hope that little girl grows up to be an engineer. By the time she comes of age, the act of invention may be something entirely new—reflecting the adoption of novel tools and the guiding forces of new social structures. Engineers, with their restless curiosity and determination to optimize the world around them, are continuously in the process of reinventing invention.

In this special issue, we bring you stories of people who are in the thick of that reinvention today. IEEE Spectrum is marking 60 years of publication this year, and we’re celebrating by highlighting both the creative act and the grindingly hard engineering work required to turn an idea into something world changing. In these pages, we take you behind the scenes of some awe-inspiring projects to reveal how technology is being made—and remade—in our time.

Inventors Are Everywhere

Invention has long been a democratic process. The economist B. Zorina Khan of Bowdoin College has noted that the U.S. Patent and Trademark Office has always endeavored to allow essentially anyone to try their hand at invention. From the beginning, the patent examiners didn’t care who the applicants were—anyone with a novel and useful idea who could pay the filing fee was officially an inventor.

This ethos continues today. It’s still possible for an individual to launch a tech startup from a garage or go on “Shark Tank” to score investors. The Swedish inventor Simone Giertz, for example, made a name for herself with YouTube videos showing off her hilariously bizarre contraptions, like an alarm clock with an arm that slapped her awake. The MIT innovation scholar Eric von Hippel has spotlighted today’s vital ecosystem of “user innovation,” in which inventors such as Giertz are motivated by their own needs and desires rather than ambitions of mass manufacturing.

But that route to invention gets you only so far, and the limits of what an individual can achieve have become starker over time. To tackle some of the biggest problems facing humanity today, inventors need a deep-pocketed government sponsor or corporate largess to muster the equipment and collective human brainpower required.

When we think about the challenges of scaling up, it’s helpful to remember Alexander Graham Bell and his collaborator Thomas Watson. “They invent this cool thing that allows them to talk between two rooms—so it’s a neat invention, but it’s basically a gadget,” says Eric Hintz, a historian of invention at the Smithsonian Institution. “To go from that to a transcontinental long-distance telephone system, they needed a lot more innovation on top of the original invention.” To scale their invention, Hintz says, Bell and his colleagues built the infrastructure that eventually evolved into Bell Labs, which became the standard-bearer for corporate R&D.

In this issue, we see engineers grappling with challenges of scale in modern problems. Consider the semiconductor technology supported by the U.S. CHIPS and Science Act, a policy initiative aimed at bolstering domestic chip production. Beyond funding manufacturing, it also provides US $11 billion for R&D, including three national centers where companies can test and pilot new technologies. As one startup tells the tale, this infrastructure will drastically speed up the lab-to-fab process.

And then there are atomic clocks, the epitome of precision timekeeping. When researchers decided to build a commercial version, they had to shift their perspective, taking a sprawling laboratory setup and reimagining it as a portable unit fit for mass production and the rigors of the real world. They had to stop optimizing for precision and instead choose the most robust laser, and the atom that would go along with it.

These technology efforts benefit from infrastructure, brainpower, and cutting-edge new tools. One tool that may become ubiquitous across industries is artificial intelligence—and it’s a tool that could further expand access to the invention arena.

What if you had a team of indefatigable assistants at your disposal, ready to scour the world’s technical literature for material that could spark an idea, or to iterate on a concept 100 times before breakfast? That’s the promise of today’s generative AI. The Swiss company Iprova is exploring whether its AI tools can automate “eureka” moments for its clients, corporations that are looking to beat their competitors to the next big idea. The serial entrepreneur Steve Blank similarly advises young startup founders to embrace AI’s potential to accelerate product development; he even imagines testing product ideas on digital twins of customers. Although it’s still early days, generative AI offers inventors tools that have never been available before.

Measuring an Invention’s Impact

If AI accelerates the discovery process, and many more patentable ideas come to light as a result, then what? As it is, more than a million patents are granted every year, and we struggle to identify the ones that will make a lasting impact. Bryan Kelly, an economist at the Yale School of Management, and his collaborators made an attempt to quantify the impact of patents by doing a technology-assisted deep dive into U.S. patent records dating back to 1840. Using natural language processing, they identified patents that introduced novel phrasing that was then repeated in subsequent patents—an indicator of radical breakthroughs. For example, Elias Howe Jr.’s 1846 patent for a sewing machine wasn’t closely related to anything that came before but quickly became the basis of future sewing-machine patents.

Another foundational patent was the one awarded to an English bricklayer in 1824 for the invention of Portland cement, which is still the key ingredient in most of the world’s concrete. As Ted C. Fishman describes in his fascinating inquiry into the state of concrete today, this seemingly stable industry is in upheaval because of its heavy carbon emissions. The AI boom is fueling a construction boom in data centers, and all those buildings require billions of tons of concrete. Fishman takes readers into labs and startups where researchers are experimenting with climate-friendly formulations of cement and concrete. Who knows which of those experiments will result in a patent that echoes down the ages?

Some engineers start their invention process by thinking about the impact they want to make on the world. The eminent Indian technologist Raghunath Anant Mashelkar, who has popularized the idea of “Gandhian engineering”, advises inventors to work backward from “what we want to achieve for the betterment of humanity,” and to create problem-solving technologies that are affordable, durable, and not only for the elite.

Durability matters: Invention isn’t just about creating something brand new. It’s also about coming up with clever ways to keep an existing thing going. Such is the case with the Hubble Space Telescope. Originally designed to last 15 years, it’s been in orbit for twice that long and has actually gotten better with age, because engineers designed the satellite to be fixable and upgradable in space.

For all the invention activity around the globe—the World Intellectual Property Organization says that 3.5 million applications for patents were filed in 2022—it may be harder to invent something useful than it used to be. Not because “everything that can be invented has been invented,” as in the apocryphal quote attributed to the unfortunate head of the U.S. patent office in 1889. Rather, because so much education and experience are required before an inventor can even understand all the dimensions of the door they’re trying to crack open, much less come up with a strategy for doing so. Ben Jones, an economist at Northwestern’s Kellogg School of Management, has shown that the average age of great technological innovators rose by about six years over the course of the 20th century. “Great innovation is less and less the provenance of the young,” Jones concluded.

Consider designing something as complex as a nuclear fusion reactor, as Tom Clynes describes in “An Off-the-Shelf Stellarator.” Fusion researchers have spent decades trying to crack the code of commercially viable fusion—it’s more akin to a calling than a career. If they succeed, they will unlock essentially limitless clean energy with no greenhouse gas emissions or meltdown danger. That’s the dream that the physicists in a lab in Princeton, N.J., are chasing. But before they even started, they first had to gain an intimate understanding of all the wrong ways to build a fusion reactor. Once the team was ready to proceed, what they created was an experimental reactor that accelerates the design-build-test cycle. With new AI tools and unprecedented computational power, they’re now searching for the best ways to create the magnetic fields that will confine the plasma within the reactor. Already, two startups have spun out of the Princeton lab, both seeking a path to commercial fusion.

The stellarator story and many other articles in this issue showcase how one innovation leads to the next, and how one invention can enable many more. The legendary Dean Kamen, best known for mechanical devices like the Segway and the prosthetic “Luke” arm, is now trying to push forward the squishy world of biological manufacturing. In an interview, Kamen explains how his nonprofit is working on the infrastructure—bioreactors, sensors, and controls—that will enable companies to explore the possibilities of growing replacement organs. You could say that he’s inventing the launchpad so others can invent the rockets.

Sometimes everyone in a research field knows where the breakthrough is needed, but that doesn’t make it any easier to achieve. Case in point: the quest for a household humanoid robot that can perform domestic chores, switching effortlessly from frying an egg to folding laundry. Roboticists need better learning software that will enable their bots to navigate the uncertainties of the real world, and they also need cheaper and lighter actuators. Major advances in these two areas would unleash a torrent of creativity and may finally bring robot butlers into our homes.

And maybe the future roboticists who make those breakthroughs will have cause to thank Marina Umaschi Bers, a technologist at Boston College who cocreated the ScratchJr programming language and the KIBO robotics kit to teach kids the basics of coding and robotics in entertaining ways. She sees engineering as a playground, a place for children to explore and create, to be goofy or grandiose. If today’s kindergartners learn to think of themselves as inventors, who knows what they’ll create tomorrow?

Video Friday is your weekly selection of awesome robotics videos, collected by your friends at IEEE Spectrum robotics. We also post a weekly calendar of upcoming robotics events for the next few months. Please send us your events for inclusion.

Humanoids 2024: 22–24 November 2024, NANCY, FRANCE

Enjoy today’s videos!

We’re hoping to get more on this from Boston Dynamics, but if you haven’t seen it yet, here’s electric Atlas doing something productive (and autonomous!).

And why not do it in a hot dog costume for Halloween, too?

[ Boston Dynamics ]

Ooh, this is exciting! Aldebaran is getting ready to release a seventh generation of NAO!

[ Aldebaran ]

Okay I found this actually somewhat scary, but Happy Halloween from ANYbotics!

[ ANYbotics ]

Happy Halloween from the Clearpath!

[ Clearpath Robotics Inc. ]

Another genuinely freaky Happy Halloween, from Boston Dynamics!

[ Boston Dynamics ]

This “urban opera” by Compagnie La Machine took place last weekend in Toulouse, featuring some truly enormous fantastical robots.

[ Compagnie La Machine ]

Thanks, Thomas!

Impressive dismount from Deep Robotics’ DR01.

[ Deep Robotics ]

Cobot juggling from Daniel Simu.

[ Daniel Simu ]

Adaptive-morphology multirotors exhibit superior versatility and task-specific performance compared to traditional multirotors owing to their functional morphological adaptability. However, a notable challenge lies in the contrasting requirements of locking each morphology for flight controllability and efficiency while permitting low-energy reconfiguration. A novel design approach is proposed for reconfigurable multirotors utilizing soft multistable composite laminate airframes.

[ Environmental Robotics Lab paper ]

This is a pitching demonstration of new Torobo. New Torobo is lighter than the older version, enabling faster motion such as throwing a ball. The new model will be available in Japan in March 2025 and overseas from October 2025 onward.

[ Tokyo Robotics ]

I’m not sure what makes this “the world’s best robotic hand for manipulation research,” but it seems solid enough.

[ Robot Era ]

And now, picking a micro cat.

[ RoCogMan Lab ]

When Arvato’s Louisville, Ky. staff wanted a robotics system that could unload freight with greater speed and safety, Boston Dynamics’ Stretch robot stood out. Stretch is a first of its kind mobile robot designed specifically to unload boxes from trailers and shipping containers, freeing up employees to focus on more meaningful tasks in the warehouse. Arvato acquired its first Stretch system this year and the robot’s impact was immediate.

[ Boston Dynamics ]

NASA’s Perseverance Mars rover used its Mastcam-Z camera to capture the silhouette of Phobos, one of the two Martian moons, as it passed in front of the Sun on Sept. 30, 2024, the 1,285th Martian day, or sol, of the mission.

[ NASA ]

Students from Howard University, Moorehouse College, and Berea College joined University of Michigan robotics students in online Robotics 102 courses for the fall ‘23 and winter ‘24 semesters. The class is part of the distributed teaching collaborative, a co-teaching initiative started in 2020 aimed at providing cutting edge robotics courses for students who would normally not have access to at their current university.

[ University of Michigan Robotics ]

Discover the groundbreaking projects and cutting-edge technology at the Robotics and Automation Summer School (RASS) hosted by Los Alamos National Laboratory. In this exclusive behind-the-scenes video, students from top universities work on advanced robotics in disciplines such as AI, automation, machine learning, and autonomous systems.

[ Los Alamos National Laboratory ]

This week’s Carnegie Mellon University Robotics Institute Seminar is from Princeton University’s Anirudha Majumdar, on “Robots That Know When They Don’t Know.”

Foundation models from machine learning have enabled rapid advances in perception, planning, and natural language understanding for robots. However, current systems lack any rigorous assurances when required to generalize to novel scenarios. For example, perception systems can fail to identify or localize unfamiliar objects, and large language model (LLM)-based planners can hallucinate outputs that lead to unsafe outcomes when executed by robots. How can we rigorously quantify the uncertainty of machine learning components such that robots know when they don’t know and can act accordingly?

[ Carnegie Mellon University Robotics Institute ]

Boston Dynamics is the master of dropping amazing robot videos with no warning, and last week, we got a surprise look at the new electric Atlas going “hands on” with a practical factory task.

This video is notable because it’s the first real look we’ve had at the new Atlas doing something useful—or doing anything at all, really, as the introductory video from back in April (the first time we saw the robot) was less than a minute long. And the amount of progress that Boston Dynamics has made is immediately obvious, with the video showing a blend of autonomous perception, full body motion, and manipulation in a practical task.

We sent over some quick questions as soon as we saw the video, and we’ve got some extra detail from Scott Kuindersma, senior director of Robotics Research at Boston Dynamics.

If you haven’t seen this video yet, what kind of robotics person are you, and also here you go:

Atlas is autonomously moving engine covers between supplier containers and a mobile sequencing dolly. The robot receives as input a list of bin locations to move parts between.

Atlas uses a machine learning (ML) vision model to detect and localize the environment fixtures and individual bins [0:36]. The robot uses a specialized grasping policy and continuously estimates the state of manipulated objects to achieve the task.

There are no prescribed or teleoperated movements; all motions are generated autonomously online. The robot is able to detect and react to changes in the environment (e.g., moving fixtures) and action failures (e.g., failure to insert the cover, tripping, environment collisions [1:24]) using a combination of vision, force, and proprioceptive sensors.

Eagle-eyed viewers will have noticed that this task is very similar to what we saw hydraulic Atlas (Atlas classic?) working on just before it retired. We probably don’t need to read too much into the differences between how each robot performs that task, but it’s an interesting comparison to make.

For more details, here’s our Q&A with Kuindersma:

How many takes did this take?

Kuindersma: We ran this sequence a couple times that day, but typically we’re always filming as we continue developing and testing Atlas. Today we’re able to run that engine cover demo with high reliability, and we’re working to expand the scope and duration of tasks like these.

Is this a task that humans currently do?

Kuindersma: Yes.

What kind of world knowledge does Atlas have while doing this task?

Kuindersma: The robot has access to a CAD model of the engine cover that is used for object pose prediction from RGB images. Fixtures are represented more abstractly using a learned keypoint prediction model. The robot builds a map of the workcell at startup which is updated on the fly when changes are detected (e.g., moving fixture).

Does Atlas’s torso have a front or back in a meaningful way when it comes to how it operates?

Kuindersma: Its head/torso/pelvis/legs do have “forward” and “backward” directions, but the robot is able to rotate all of these relative to one another. The robot always knows which way is which, but sometimes the humans watching lose track.

Are the head and torso capable of unlimited rotation?

Kuindersma: Yes, many of Atlas’s joints are continuous.

How long did it take you folks to get used to the way Atlas moves?

Kuindersma: Atlas’s motions still surprise and delight the team.

OSHA recommends against squatting because it can lead to workplace injuries. How does Atlas feel about that?

Kuindersma: As might be evident by some of Atlas’s other motions, the kinds of behaviors that might be injurious for humans might be perfectly fine for robots.

Can you describe exactly what process Atlas goes through at 1:22?

Kuindersma: The engine cover gets caught on the fabric bins and triggers a learned failure detector on the robot. Right now this transitions into a general-purpose recovery controller, which results in a somewhat jarring motion (we will improve this). After recovery, the robot retries the insertion using visual feedback to estimate the state of both the part and fixture.

Were there other costume options you considered before going with the hot dog?

Kuindersma: Yes, but marketing wants to save them for next year.

How many important sensors does the hot dog costume occlude?

Kuindersma: None. The robot is using cameras in the head, proprioceptive sensors, IMU, and force sensors in the wrists and feet. We did have to cut the costume at the top so the head could still spin around.

Why are pickles always causing problems?

Kuindersma: Because pickles are pesky, polarizing pests.

Research expeditions conducted at sea using a rotating gravity machine and microscope found that the Earth’s oceans may not be absorbing as much carbon as researchers have long thought.

Oceans are believed to absorb roughly 26 percent of global carbon dioxide emissions by drawing down CO₂ from the atmosphere and locking it away. In this system, CO₂ enters the ocean, where phytoplankton and other organisms consume about 70 percent of it. When these organisms eventually die, their soft, small structures sink to the bottom of the ocean in what looks like an underwater snowfall.

This “marine snow” pulls carbon away from the surface of the ocean and sequesters it in the depths for millennia, which enables the surface waters to draw down more CO₂ from the air. It’s one of Earth’s best natural carbon-removal systems. It’s so effective at keeping atmospheric CO₂ levels in check that many research groups are trying to enhance the process with geoengineering techniques.

But the new study, published on 11 October in Science, found that the sinking particles don’t fall to the ocean floor as quickly as researchers thought. Using a custom gravity machine that simulated marine snow’s native environment, the study’s authors observed that the particles produce mucus tails that act like parachutes, putting the brakes on their descent—sometimes even bringing them to a standstill.

The physical drag leaves carbon lingering in the upper hydrosphere, rather than being safely sequestered in deeper waters. Living organisms can then consume the marine snow particles and respire their carbon back into the sea. Ultimately, this impedes the rate at which the ocean draws down and sequesters additional CO₂ from the air.

The implications are grim: Scientists’ best estimates of how much CO₂ the Earth’s oceans sequester could be way off. “We’re talking roughly hundreds of gigatonnes of discrepancy if you don’t include these marine snow tails,” says Manu Prakash, a bioengineer at Stanford University and one of the paper’s authors. The work was conducted by researchers at Stanford, Rutgers University in New Jersey, and Woods Hole Oceanographic Institution in Massachusetts.

Oceans Absorb Less CO₂ Than Expected

Researchers for years have been developing numerical models to estimate marine carbon sequestration. Those models will need to be adjusted for the slower sinking speed of marine snow, Prakash says.

The findings also have implications for startups in the fledgling marine carbon geoengineering field. These companies use techniques such as ocean alkalinity enhancement to augment the ocean’s ability to sequester carbon. Their success depends, in part, on using numerical models to prove to investors and the public that their techniques work. But their estimates are only as good as the models they use, and the scientific community’s confidence in them.

“We’re talking roughly hundreds of gigatonnes of discrepancy if you don’t include these marine snow tails.” —Manu Prakash, Stanford University

The Stanford researchers made the discovery on an expedition off the coast of Maine. There, they collected marine samples by hanging traps from their boat 80 meters deep. After pulling up a sample, the researchers quickly analyzed the contents while still on board the ship using their wheel-shaped machine and microscope.

The researchers built a microscope with a spinning wheel that simulates marine snow falling through sea water over longer distances than would otherwise be practical.Prakash Lab/Stanford

The device simulates the organisms’ vertical travel over long distances. Samples go into a wheel about the size of a vintage film reel. The wheel spins constantly, allowing suspended marine-snow particles to sink while a camera captures their every move.

The apparatus adjusts for temperature, light, and pressure to emulate marine conditions. Computational tools assess flow around the sinking particles and custom software removes noise in the data from the ship’s vibrations. To accommodate for the tilt and roll of the ship, the researchers mounted the device on a two-axis gimbal.

Slower Marine Snow Reduces Carbon Sequestration

With this setup, the team observed that sinking marine snow generates an invisible halo-shaped comet tail made of viscoelastic transparent exopolymer—a mucus-like parachute. They discovered the invisible tail by adding small beads to the seawater sample in the wheel, and analyzing the way they flowed around the marine snow. “We found that the beads were stuck in something invisible trailing behind the sinking particles,” says Rahul Chajwa, a bioengineering postdoctoral fellow at Stanford.

The tail introduces drag and buoyancy, doubling the amount of time marine snow spends in the upper 100 meters of the ocean, the researchers concluded. “This is the sedimentation law we should be following,” says Prakash, who hopes to get the results into climate models.

The study will likely help models project carbon export—the process of transporting CO₂ from the atmosphere to the deep ocean, says Lennart Bach, a marine biochemist at the University of Tasmania in Australia, who was not involved with the research. “The methodology they developed is very exciting and it’s great to see new methods coming into this research field,” he says.

But Bach cautions against extrapolating the results too far. “I don’t think the study will change the numbers on carbon export as we know them right now,” because these numbers are derived from empirical methods that would have unknowingly included the effects of the mucus tail, he says.

Marine snow may be slowed by “parachutes” of mucus while sinking, potentially lowering the rate at which the global ocean can sequester carbon in the depths.Prakash Lab/Stanford

Prakash and his team came up with the idea for the microscope while conducting research on a human parasite that can travel dozens of meters. “We would make 5- to 10-meter-tall microscopes, and one day, while packing for a trip to Madagascar, I had this ‘aha’ moment,” says Prakash. “I was like: Why are we packing all these tubes? What if the two ends of these tubes were connected?”

The group turned their linear tube into a closed circular channel—a hamster wheel approach to observing microscopic particles. Over five expeditions at sea, the team further refined the microscope’s design and fluid mechanics to accommodate marine samples, often tackling the engineering while on the boat and adjusting for flooding and high seas.

In addition to the sedimentation physics of marine snow, the team also studies other plankton that may affect climate and carbon-cycle models. On a recent expedition off the coast of Northern California, the group discovered a cell with silica ballast that makes marine snow sink like a rock, Prakash says.

The crafty gravity machine is one of Prakash’s many frugal inventions, which include an origami-inspired paper microscope, or “foldscope,” that can be attached to a smartphone, and a paper-and-string biomedical centrifuge dubbed a “paperfuge.”

Last week the organization tasked with running the the biggest chunk of U.S. CHIPS Act’s US $13 billion R&D program made some significant strides: The National Semiconductor Technology Center (NSTC) released a strategic plan and selected the sites of two of three planned facilities and released a new strategic plan. The locations of the two sites—a “design and collaboration” center in Sunnyvale, Calif., and a lab devoted to advancing the leading edge of chipmaking, in Albany, N.Y.—build on an existing ecosystem at each location, experts say. The location of the third planned center—a chip prototyping and packaging site that could be especially critical for speeding semiconductor startups—is still a matter of speculation.

“The NSTC represents a once-in-a-generation opportunity for the U.S. to accelerate the pace of innovation in semiconductor technology,” Deirdre Hanford, CEO of Natcast, the nonprofit that runs the NSTC centers, said in a statement. According to the strategic plan, which covers 2025 to 2027, the NSTC is meant to accomplish three goals: extend U.S. technology leadership, reduce the time and cost to prototype, and build and sustain a semiconductor workforce development ecosystem. The three centers are meant to do a mix of all three.

New York gets extreme ultraviolet lithography

NSTC plans to direct $825 million into the Albany project. The site will be dedicated to extreme ultraviolet lithography, a technology that’s essential to making the most advanced logic chips. The Albany Nanotech Complex, which has already seen more than $25 billion in investments from the state and industry partners over two decades, will form the heart of the future NSTC center. It already has an EUV lithography machine on site and has begun an expansion to install a next-generation version, called high-NA EUV, which promises to produce even finer chip features. Working with a tool recently installed in Europe, IBM, a long-time tenant of the Albany research facility, reported record yields of copper interconnects built every 21 nanometers, a pitch several nanometers tighter than possible with ordinary EUV.

“It’s fulfilling to see that this ecosystem can be taken to the national and global level through CHIPS Act funding,” said Mukesh Khare, general manager of IBM’s semiconductors division, speaking from the future site of the NSTC EUV center. “It’s the right time, and we have all the ingredients.”

While only a few companies are capable of manufacturing cutting edge logic using EUV, the impact of the NSTC center will be much broader, Khare argues. It will extend down as far as early-stage startups with ideas or materials for improving the chipmaking process “An EUV R&D center doesn’t mean just one machine,” says Khare. “It needs so many machines around it… It’s a very large ecosystem.”

Silicon Valley lands the design center

The design center is tasked with conducting advanced research in chip design, electronic design automation (EDA), chip and system architectures, and hardware security. It will also host the NSTC’s design enablement gateway—a program that provides NSTC members with a secure, cloud-based access to design tools, reference processes and designs, and shared data sets, with the goal of reducing the time and cost of design. Additionally, it will house workforce development, member convening, and administration functions.

Situating the design center in Silicon Valley, with its concentration of research universities, venture capital, and workforce, seems like the obvious choice to many experts. “I can’t think of a better place,” says Patrick Soheili, co-founder of interconnect technology startup Eliyan, which is based in Santa Clara, Calif.

Abhijeet Chakraborty, vice president of engineering in the technology and product group at Silicon Valley-based Synopsys, a leading maker of EDA software, sees Silicon Valley’s expansive tech ecosystem as one of its main advantages in landing the NSTC’s design center. The region concentrates companies and researchers involved in the whole spectrum of the industry from semiconductor process technology to cloud software.

Access to such a broad range of industries is increasingly important for chip design startups, he says. “To design a chip or component these days you need to go from concept to design to validation in an environment that takes care of the entire stack,” he says. It’s prohibitively expensive for a startup to do that alone, so one of Chakraborty’s hopes for the design center is that it will help startups access the design kits and other data needed to operate in this new environment.

Packaging and prototyping still to come

A third promised center for prototyping and packaging is still to come. “The big question is where does the packaging and prototyping go?” says Mark Granahan, cofounder and CEO of Pennsylvania-based power semiconductor startup Ideal Semiconductor. “To me that’s a great opportunity.” He points out that because there is so little packaging technology infrastructure in the United States, any ambitious state or region should have a shot at hosting such a center. One of the original intentions of the act, after all, was to expand the number of regions of the country that are involved in the semiconductor industry.

But that hasn’t stopped some already tech-heavy regions from wanting it. “Oregon offers the strongest ecosystem for such a facility,” a spokesperson for Intel, whose technology development is done there. “The state is uniquely positioned to contribute to the success of the NSTC and help drive technological advancements in the U.S. semiconductor industry.”

As NSTC makes progress, Granahan’s concern is that bureaucracy will expand with it and slow efforts to boost the U.S. chip industry. Already the layers of control are multiplying. The Chips Office at the National Institute of Standards and Technology executes the Act. The NSTC is administered by the nonprofit Natcast, which directs the EUV center, which is in a facility run by another nonprofit, NY CREATES. “We want these things to be agile and make local decisions.”

EPICS in IEEE, a service learning program for university students supported by IEEE Educational Activities, offers students opportunities to engage with engineering professionals and mentors, local organizations, and technological innovation to address community-based issues.

The following two environmentally focused projects demonstrate the value of teamwork and direct involvement with project stakeholders. One uses smart biodigesters to better manage waste in Colombia’s rural areas. The other is focused on helping Turkish olive farmers protect their trees from climate change effects by providing them with a warning system that can identify growing problems.

No time to waste in rural Colombia

Proper waste management is critical to a community’s living conditions. In rural La Vega, Colombia, the lack of an effective system has led to contaminated soil and water, an especially concerning issue because the town’s economy relies heavily on agriculture.

The Smart Biodigesters for a Better Environment in Rural Areas project brought students together to devise a solution.

Vivian Estefanía Beltrán, a Ph.D. student at the Universidad del Rosario in Bogotá, addressed the problem by building a low-cost anaerobic digester that uses an instrumentation system to break down microorganisms into biodegradable material. It reduces the amount of solid waste, and the digesters can produce biogas, which can be used to generate electricity.

“Anaerobic digestion is a natural biological process that converts organic matter into two valuable products: biogas and nutrient-rich soil amendments in the form of digestate,” Beltrán says. “As a by-product of our digester’s operation, digestate is organic matter that can’t be transferred into biogas but can be used as a soil amendment for our farmers’ crops, such as coffee.

“While it may sound easy, the process is influenced by a lot of variables. The support we’ve received from EPICS in IEEE is important because it enables us to measure these variables, such as pH levels, temperature of the reactor, and biogas composition [methane and hydrogen sulfide]. The system allows us to make informed decisions that enhance the safety, quality, and efficiency of the process for the benefit of the community.”

The project was a collaborative effort among Universidad del Rosario students, a team of engineering students from Escuela Tecnológica Instituto Técnico Central, Professor Carlos Felipe Vergara, and members of Junta de Acción Comunal (Vereda La Granja), which aims to help residents improve their community.

“It’s been a great experience to see how individuals pursuing different fields of study—from engineering to electronics and computer science—can all work and learn together on a project that will have a direct positive impact on a community.” —Vivian Estefanía Beltrán

Beltrán worked closely with eight undergraduate students and three instructors—Maria Fernanda Gómez, Andrés Pérez Gordillo (the instrumentation group leader), and Carlos Felipe Vergara-Ramirez—as well as IEEE Graduate Student Member Nicolás Castiblanco (the instrumentation group coordinator).

The team constructed and installed their anaerobic digester system in an experimental station in La Vega, a town located roughly 53 kilometers northwest of Bogotá.

“This digester is an important innovation for the residents of La Vega, as it will hopefully offer a productive way to utilize the residual biomass they produce to improve quality of life and boost the economy,” Beltrán says. Soon, she adds, the system will be expanded to incorporate high-tech sensors that automatically monitor biogas production and the digestion process.

“For our students and team members, it’s been a great experience to see how individuals pursuing different fields of study—from engineering to electronics and computer science—can all work and learn together on a project that will have a direct positive impact on a community. It enables all of us to apply our classroom skills to reality,” she says. “The funding we’ve received from EPICS in IEEE has been crucial to designing, proving, and installing the system.”

The project also aims to support the development of a circular economy, which reuses materials to enhance the community’s sustainability and self-sufficiency.

Protecting olive groves in Türkiye

Türkiye is one of the world’s leading producers of olives, but the industry has been challenged in recent years by unprecedented floods, droughts, and other destructive forces of nature resulting from climate change. To help farmers in the western part of the country monitor the health of their olive trees, a team of students from Istanbul Technical University developed an early-warning system to identify irregularities including abnormal growth.

“Almost no olives were produced last year using traditional methods, due to climate conditions and unusual weather patterns,” says Tayfun Akgül, project leader of the Smart Monitoring of Fruit Trees in Western Türkiye initiative.

“Our system will give farmers feedback from each tree so that actions can be taken in advance to improve the yield,” says Akgül, an IEEE senior member and a professor in the university’s electronics and communication engineering department.

“We’re developing deep-learning techniques to detect changes in olive trees and their fruit so that farmers and landowners can take all necessary measures to avoid a low or damaged harvest,” says project coordinator Melike Girgin, a Ph.D. student at the university and an IEEE graduate student member.

Using drones outfitted with 360-degree optical and thermal cameras, the team collects optical, thermal, and hyperspectral imaging data through aerial methods. The information is fed into a cloud-based, open-source database system.

Akgül leads the project and teaches the team skills including signal and image processing and data collection. He says regular communication with community-based stakeholders has been critical to the project’s success.

“There are several farmers in the village who have helped us direct our drone activities to the right locations,” he says. “Their involvement in the project has been instrumental in helping us refine our process for greater effectiveness.

“For students, classroom instruction is straightforward, then they take an exam at the end. But through our EPICS project, students are continuously interacting with farmers in a hands-on, practical way and can see the results of their efforts in real time.”

Looking ahead, the team is excited about expanding the project to encompass other fruits besides olives. The team also intends to apply for a travel grant from IEEE in hopes of presenting its work at a conference.

“We’re so grateful to EPICS in IEEE for this opportunity,” Girgin says. “Our project and some of the technology we required wouldn’t have been possible without the funding we received.”

A purpose-driven partnership

The IEEE Standards Association sponsored both of the proactive environmental projects.

“Technical projects play a crucial role in advancing innovation and ensuring interoperability across various industries,” says Munir Mohammed, IEEE SA senior manager of product development and market engagement. “These projects not only align with our technical standards but also drive technological progress, enhance global collaboration, and ultimately improve the quality of life for communities worldwide.”

For more information on the program or to participate in service-learning projects, visit EPICS in IEEE.

On 7 November, this article was updated from an earlier version.

In 6G telecom research today, a crucial portion of wireless spectrum has been neglected: the Frequency Range 3, or FR3, band. The shortcoming is partly due to a lack of viable software and hardware platforms for studying this region of spectrum, ranging from approximately 6 to 24 gigahertz. But a new, open-source wireless research kit is changing that equation. And research conducted using that kit, presented last week at a leading industry conference, offers proof of viability of this spectrum band for future 6G networks.

In fact, it’s also arguably signaling a moment of telecom industry re-evaluation. The high-bandwidth 6G future, according to these folks, may not be entirely centered around difficult millimeter wave-based technologies. Instead, 6G may leave plenty of room for higher-bandwidth microwave spectrum tech that is ultimately more familiar and accessible.

The FR3 band is a region of microwave spectrum just shy of millimeter-wave frequencies (30 to 300 GHz). FR3 is also already very popular today for satellite Internet and military communications. For future 5G and 6G networks to share the FR3 band with incumbent players would require telecom networks nimble enough to perform regular, rapid-response spectrum-hopping.

Yet spectrum-hopping might still be an easier problem to solve than those posed by the inherent physical shortcomings of some portions of millimeter-wave spectrum—shortcomings that include limited range, poor penetration, line-of-sight operations, higher power requirements, and susceptibility to weather.

Pi-Radio’s New Face

Earlier this year, the Brooklyn, N.Y.-based startup Pi-Radio—a spinoff from New York University’s Tandon School of Engineering—released a wireless spectrum hardware and software kit for telecom research and development. Pi-Radio’s FR-3 is a software-defined radio system developed for the FR3 band specifically, says company co-founder Sundeep Rangan.

“Software-defined radio is basically a programmable platform to experiment and build any type of wireless technology,” says Rangan, who is also the associate director of NYU Wireless. “In the early stages when developing systems, all researchers need these.”

For instance, the Pi-Radio team presented one new research finding that infers direction to an FR3 antenna from measurements taken by a mobile Pi-Radio receiver—presented at the IEEE Signal Processing Society‘s Asilomar Conference on Signals, Systems and Computers in Pacific Grove, Calif. on 30 October.

According to Pi-Radio co-founder Marco Mezzavilla, who’s also an associate professor at the Polytechnic University of Milan, the early-stage FR3 research that the team presented at Asilomar will enable researchers “to capture [signal] propagation in these frequencies and will allow us to characterize it, understand it, and model it... And this is the first stepping stone towards designing future wireless systems at these frequencies.”

There’s a good reason researchers have recently rediscovered FR3, says Paolo Testolina, postdoctoral research fellow at Northeastern University’s Institute for the Wireless Internet of Things unaffiliated with the current research effort. “The current scarcity of spectrum for communications is driving operators and researchers to look in this band, where they believe it is possible to coexist with the current incumbents,” he says. “Spectrum sharing will be key in this band.”

Rangan notes that the work on which Pi-Radio was built has been published earlier this year both on the more foundational aspects of building networks in the FR3 band as well as the specific implementation of Pi-Radio’s unique, frequency-hopping research platform for future wireless networks. (Both papers were published in IEEE journals.)

“If you have frequency hopping, that means you can get systems that are resilient to blockage,” Rangan says. “But even, potentially, if it was attacked or compromised in any other way, this could actually open up a new type of dimension that we typically haven’t had in the cellular infrastructure.” The frequency-hopping that FR3 requires for wireless communications, in other words, could introduce a layer of hack-proofing that might potentially strengthen the overall network.

Complement, Not Replacement

The Pi-Radio team stresses, however, that FR3 would not supplant or supersede other new segments of wireless spectrum. There are, for instance, millimeter wave 5G deployments already underway today that will no doubt expand in scope and performance into the 6G future. That said, the ways that FR3 expand future 5G and 6G spectrum usage is an entirely unwritten chapter: Whether FR3 as a wireless spectrum band fizzles, or takes off, or finds a comfortable place somewhere in between depends in part on how it’s researched and developed now, the Pi-Radio team says.

“We’re at this tipping point where researchers and academics actually are empowered by the combination of this cutting-edge hardware with open-source software,” Mezzavilla says. “And that will enable the testing of new features for communications in these new frequency bands.” (Mezzavilla credits the National Telecommunications and Information Administration for recognizing the potential of FR3, and for funding the group’s research.)

By contrast, millimeter-wave 5G and 6G research has to date been bolstered, the team says, by the presence of a wide range of millimeter-wave software-defined radio (SDR) systems and other research platforms.

“Companies like Qualcomm, Samsung, Nokia, they actually had excellent millimeter wave development platforms,” Rangan says. “But they were in-house. And the effort it took to build one—an SDR at a university lab—was sort of insurmountable.”

So releasing an inexpensive open-source SDR in the FR3 band, Mezzavilla says, could jump start a whole new wave of 6G research.

“This is just the starting point,” Mezzavilla says. “From now on we’re going to build new features—new reference signals, new radio resource control signals, near-field operations... We’re ready to ship these yellow boxes to other academics around the world to test new features and test them quickly, before 6G is even remotely near us.”

This story was updated on 7 November 2024 to include detail about funding from the National Telecommunications and Information Administration.

Video Friday is your weekly selection of awesome robotics videos, collected by your friends at IEEE Spectrum robotics. We also post a weekly calendar of upcoming robotics events for the next few months. Please send us your events for inclusion.

Humanoids 2024: 22–24 November 2024, NANCY, FRANCE

Enjoy today’s videos!

Just when I thought quadrupeds couldn’t impress me anymore...

[ Unitree Robotics ]

Researchers at Meta FAIR are releasing several new research artifacts that advance robotics and support our goal of reaching advanced machine intelligence (AMI). These include Meta Sparsh, the first general-purpose encoder for vision-based tactile sensing that works across many tactile sensors and many tasks; Meta Digit 360, an artificial fingertip-based tactile sensor that delivers detailed touch data with human-level precision and touch-sensing; and Meta Digit Plexus, a standardized platform for robotic sensor connections and interactions that enables seamless data collection, control and analysis over a single cable.

[ Meta ]

The first bimanual Torso created at Clone includes an actuated elbow, cervical spine (neck), and anthropomorphic shoulders with the sternoclavicular, acromioclavicular, scapulothoracic and glenohumeral joints. The valve matrix fits compactly inside the ribcage. Bimanual manipulation training is in progress.

[ Clone Inc. ]

Equipped with a new behavior architecture, Nadia navigates and traverses many types of doors autonomously. Nadia also demonstrates robustness to failed grasps and door opening attempts by automatically retrying and continuing. We present the robot with pull and push doors, four types of opening mechanisms, and even spring-loaded door closers. A deep neural network and door plane estimator allow Nadia to identify and track the doors.

[ Paper preprint by authors from Florida Institute for Human and Machine Cognition ]

Thanks, Duncan!

In this study, we integrate the musculoskeletal humanoid Musashi with the wire-driven robot CubiX, capable of connecting to the environment, to form CubiXMusashi. This combination addresses the shortcomings of traditional musculoskeletal humanoids and enables movements beyond the capabilities of other humanoids. CubiXMusashi connects to the environment with wires and drives by winding them, successfully achieving movements such as pull-up, rising from a lying pose, and mid-air kicking, which are difficult for Musashi alone.

[ CubiXMusashi, JSK Robotics Laboratory, University of Tokyo ]

Thanks, Shintaro!

An old boardwalk seems like a nightmare for any robot with flat feet.

[ Agility Robotics ]

This paper presents a novel learning-based control framework that uses keyframing to incorporate high-level objectives in natural locomotion for legged robots. These high-level objectives are specified as a variable number of partial or complete pose targets that are spaced arbitrarily in time. Our proposed framework utilizes a multi-critic reinforcement learning algorithm to effectively handle the mixture of dense and sparse rewards. In the experiments, the multi-critic method significantly reduces the effort of hyperparameter tuning compared to the standard single-critic alternative. Moreover, the proposed transformer-based architecture enables robots to anticipate future goals, which results in quantitative improvements in their ability to reach their targets.

[ Disney Research paper ]

Human-like walking where that human is the stompiest human to ever human its way through Humanville.

[ Engineai ]

We present the first static-obstacle avoidance method for quadrotors using just an onboard, monocular event camera. Quadrotors are capable of fast and agile flight in cluttered environments when piloted manually, but vision-based autonomous flight in unknown environments is difficult in part due to the sensor limitations of traditional onboard cameras. Event cameras, however, promise nearly zero motion blur and high dynamic range, but produce a large volume of events under significant ego-motion and further lack a continuous-time sensor model in simulation, making direct sim-to-real transfer not possible.

[ Paper University of Pennsylvania and University of Zurich ]

Cross-embodiment imitation learning enables policies trained on specific embodiments to transfer across different robots, unlocking the potential for large-scale imitation learning that is both cost-effective and highly reusable. This paper presents LEGATO, a cross-embodiment imitation learning framework for visuomotor skill transfer across varied kinematic morphologies. We introduce a handheld gripper that unifies action and observation spaces, allowing tasks to be defined consistently across robots.

[ LEGATO ]

The 2024 Xi’an Marathon has kicked off! STAR1, the general-purpose humanoid robot from Robot Era, joins runners in this ancient yet modern city for an exciting start!

[ Robot Era ]

In robotics, there are valuable lessons for students and mentors alike. Watch how the CyberKnights, a FIRST robotics team champion sponsored by RTX, with the encouragement of their RTX mentor, faced challenges after a poor performance and scrapped its robot to build a new one in just nine days.

[ CyberKnights ]

In this special video, PAL Robotics takes you behind the scenes of our 20th-anniversary celebration, a memorable gathering with industry leaders and visionaries from across robotics and technology. From inspiring speeches to milestone highlights, the event was a testament to our journey and the incredible partnerships that have shaped our path.

[ PAL Robotics ]

Thanks, Rugilė!

Finished chips coming in from the foundry are subject to a battery of tests. For those destined for critical systems in cars, those tests are particularly extensive and can add 5 to 10 percent to the cost of a chip. But do you really need to do every single test?

Engineers at NXP have developed a machine-learning algorithm that learns the patterns of test results and figures out the subset of tests that are really needed and those that they could safely do without. The NXP engineers described the process at the IEEE International Test Conference in San Diego last week.

NXP makes a wide variety of chips with complex circuitry and advanced chip-making technology, including inverters for EV motors, audio chips for consumer electronics, and key-fob transponders to secure your car. These chips are tested with different signals at different voltages and at different temperatures in a test process called continue-on-fail. In that process, chips are tested in groups and are all subjected to the complete battery, even if some parts fail some of the tests along the way.

Chips were subject to between 41 and 164 tests, and the algorithm was able to recommend removing 42 to 74 percent of those tests.

“We have to ensure stringent quality requirements in the field, so we have to do a lot of testing,” says Mehul Shroff, an NXP Fellow who led the research. But with much of the actual production and packaging of chips outsourced to other companies, testing is one of the few knobs most chip companies can turn to control costs. “What we were trying to do here is come up with a way to reduce test cost in a way that was statistically rigorous and gave us good results without compromising field quality.”

A Test Recommender System

Shroff says the problem has certain similarities to the machine learning-based recommender systems used in e-commerce. “We took the concept from the retail world, where a data analyst can look at receipts and see what items people are buying together,” he says. “Instead of a transaction receipt, we have a unique part identifier and instead of the items that a consumer would purchase, we have a list of failing tests.”

The NXP algorithm then discovered which tests fail together. Of course, what’s at stake for whether a purchaser of bread will want to buy butter is quite different from whether a test of an automotive part at a particular temperature means other tests don’t need to be done. “We need to have 100 percent or near 100 percent certainty,” Shroff says. “We operate in a different space with respect to statistical rigor compared to the retail world, but it’s borrowing the same concept.”

As rigorous as the results are, Shroff says that they shouldn’t be relied upon on their own. You have to “make sure it makes sense from engineering perspective and that you can understand it in technical terms,” he says. “Only then, remove the test.”

Shroff and his colleagues analyzed data obtained from testing seven microcontrollers and applications processors built using advanced chipmaking processes. Depending on which chip was involved, they were subject to between 41 and 164 tests, and the algorithm was able to recommend removing 42 to 74 percent of those tests. Extending the analysis to data from other types of chips led to an even wider range of opportunities to trim testing.

The algorithm is a pilot project for now, and the NXP team is looking to expand it to a broader set of parts, reduce the computational overhead, and make it easier to use.

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