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How Newsom hiked fuel prices — and got away with it
Brazil seeks to calm fears it will run out of beds for COP30
EU climate chief expects pension funds to help revamp grids
Model predicts long-term effects of nuclear waste on underground disposal systems
As countries across the world experience a resurgence in nuclear energy projects, the questions of where and how to dispose of nuclear waste remain as politically fraught as ever. The United States, for instance, has indefinitely stalled its only long-term underground nuclear waste repository. Scientists are using both modeling and experimental methods to study the effects of underground nuclear waste disposal and ultimately, they hope, build public trust in the decision-making process.
New research from scientists at MIT, Lawrence Berkeley National Lab, and the University of Orléans makes progress in that direction. The study shows that simulations of underground nuclear waste interactions, generated by new, high-performance-computing software, aligned well with experimental results from a research facility in Switzerland.
The study, which was co-authored by MIT PhD student Dauren Sarsenbayev and Assistant Professor Haruko Wainwright, along with Christophe Tournassat and Carl Steefel, appears in the journal PNAS.
“These powerful new computational tools, coupled with real-world experiments like those at the Mont Terri research site in Switzerland, help us understand how radionuclides will migrate in coupled underground systems,” says Sarsenbayev, who is first author of the new study.
The authors hope the research will improve confidence among policymakers and the public in the long-term safety of underground nuclear waste disposal.
“This research — coupling both computation and experiments — is important to improve our confidence in waste disposal safety assessments,” says Wainwright. “With nuclear energy re-emerging as a key source for tackling climate change and ensuring energy security, it is critical to validate disposal pathways.”
Comparing simulations with experiments
Disposing of nuclear waste in deep underground geological formations is currently considered the safest long-term solution for managing high-level radioactive waste. As such, much effort has been put into studying the migration behaviors of radionuclides from nuclear waste within various natural and engineered geological materials.
Since its founding in 1996, the Mont Terri research site in northern Switzerland has served as an important test bed for an international consortium of researchers interested in studying materials like Opalinus clay — a thick, water-tight claystone abundant in the tunneled areas of the mountain.
“It is widely regarded as one of the most valuable real-world experiment sites because it provides us with decades of datasets around the interactions of cement and clay, and those are the key materials proposed to be used by countries across the world for engineered barrier systems and geological repositories for nuclear waste,” explains Sarsenbayev.
For their study, Sarsenbayev and Wainwright collaborated with co-authors Tournassat and Steefel, who have developed high-performance computing software to improve modeling of interactions between the nuclear waste and both engineered and natural materials.
To date, several challenges have limited scientists’ understanding of how nuclear waste reacts with cement-clay barriers. For one thing, the barriers are made up of irregularly mixed materials deep underground. Additionally, the existing class of models commonly used to simulate radionuclide interactions with cement-clay do not take into account electrostatic effects associated with the negatively charged clay minerals in the barriers.
Tournassat and Steefel’s new software accounts for electrostatic effects, making it the only one that can simulate those interactions in three-dimensional space. The software, called CrunchODiTi, was developed from established software known as CrunchFlow and was most recently updated this year. It is designed to be run on many high-performance computers at once in parallel.
For the study, the researchers looked at a 13-year-old experiment, with an initial focus on cement-clay rock interactions. Within the last several years, a mix of both negatively and positively charged ions were added to the borehole located near the center of the cement emplaced in the formation. The researchers focused on a 1-centimeter-thick zone between the radionuclides and cement-clay referred to as the “skin.” They compared their experimental results to the software simulation, finding the two datasets aligned.
“The results are quite significant because previously, these models wouldn’t fit field data very well,” Sarsenbayev says. “It’s interesting how fine-scale phenomena at the ‘skin’ between cement and clay, the physical and chemical properties of which changes over time, could be used to reconcile the experimental and simulation data.”
The experimental results showed the model successfully accounted for electrostatic effects associated with the clay-rich formation and the interaction between materials in Mont Terri over time.
“This is all driven by decades of work to understand what happens at these interfaces,” Sarsenbayev says. “It’s been hypothesized that there is mineral precipitation and porosity clogging at this interface, and our results strongly suggest that.”
“This application requires millions of degrees of freedom because these multibarrier systems require high resolution and a lot of computational power,” Sarsenbayev says. “This software is really ideal for the Mont Terri experiment.”
Assessing waste disposal plans
The new model could now replace older models that have been used to conduct safety and performance assessments of underground geological repositories.
“If the U.S. eventually decides to dispose nuclear waste in a geological repository, then these models could dictate the most appropriate materials to use,” Sarsenbayev says. “For instance, right now clay is considered an appropriate storage material, but salt formations are another potential medium that could be used. These models allow us to see the fate of radionuclides over millennia. We can use them to understand interactions at timespans that vary from months to years to many millions of years.”
Sarsenbayev says the model is reasonably accessible to other researchers and that future efforts may focus on the use of machine learning to develop less computationally expensive surrogate models.
Further data from the experiment will be available later this month. The team plans to compare those data to additional simulations.
“Our collaborators will basically get this block of cement and clay, and they’ll be able to run experiments to determine the exact thickness of the skin along with all of the minerals and processes present at this interface,” Sarsenbayev says. “It’s a huge project and it takes time, but we wanted to share initial data and this software as soon as we could.”
For now, the researchers hope their study leads to a long-term solution for storing nuclear waste that policymakers and the public can support.
“This is an interdisciplinary study that includes real world experiments showing we’re able to predict radionuclides’ fate in the subsurface,” Sarsenbayev says. “The motto of MIT’s Department of Nuclear Science and Engineering is ‘Science. Systems. Society.’ I think this merges all three domains.”
Warmer ecosystems save their breath
Nature Climate Change, Published online: 18 July 2025; doi:10.1038/s41558-025-02382-2
Land stores vast amounts of carbon, and how much of it is released as temperatures rise could accelerate climate change. Now research shows ecosystems are more adaptable to climate warming than previously thought, potentially reducing future carbon–climate feedbacks.Thermal adaptation of respiration in terrestrial ecosystems alleviates carbon loss
Nature Climate Change, Published online: 18 July 2025; doi:10.1038/s41558-025-02377-z
Terrestrial ecosystems are expected to release more carbon under warming due to temperature-driven increases in ecosystem respiration. Here the authors use eddy covariance data to show that respiration may adapt to warmer temperatures and carbon losses may be lower than expected.We Support Wikimedia Foundation’s Challenge to UK’s Online Safety Act
The Electronic Frontier Foundation and ARTICLE 19 strongly support the Wikimedia Foundation’s legal challenge to the categorization regulations of the United Kingdom’s Online Safety Act.
The Foundation – the non-profit that operates Wikipedia and other Wikimedia projects – announced its legal challenge earlier this year, arguing that the regulations endanger Wikipedia and the global community of volunteer contributors who create the information on the site. The High Court of Justice in London will hear the challenge on July 22 and 23.
EFF and ARTICLE 19 agree with the Foundation’s argument that, if enforced, the Category 1 duties - the OSA’s most stringent obligations – would undermine the privacy and safety of Wikipedia’s volunteer contributors, expose the site to manipulation and divert essential resources from protecting people and improving the site. For example, because the law requires Category 1 services to allow users to block all unverified users from editing any content they post, the law effectively requires the Foundation to verify the identity of many Wikipedia contributors. However, that compelled verification undermines the privacy that keeps the site’s volunteers safe.
Wikipedia is the world’s most trusted and widely used encyclopedia, with users across the word accessing its wealth of information and participating in free information exchange through the site. The OSA must not be allowed to diminish it and jeopardize the volunteers on which it depends.
Beyond the issues raised in Wikimedia’s lawsuit, EFF and ARTICLE 19 emphasize that the Online Safety Act poses a serious threat to freedom of expression and privacy online, both in the U.K. and globally. Several key provisions of the law become operational July 25, and some companies already are rolling out age-verification mechanisms which undermine free expression and privacy rights of both adults and minors.
Helping cities evolve
Growing up in Paris, Vincent Rollet was exposed to the world beyond France from an early age. His dad was an engineer who traveled around the globe to set up electrical infrastructure, and he moved the family to the United States for two years when Rollet was a small child. His father’s work sparked Rollet’s interest in international development and growth. “It made me want to see and learn how things work in other parts of the world,” he says.
Today, Rollet is a fifth-year PhD student in MIT’s Department of Economics, studying how cities evolve — and how they may become constrained by their past. “Cities constantly need to adapt to economic changes,” he explains. “For example, you might need more housing as populations grow, or want to transform manufacturing spaces into modern lab facilities. With the rise of remote work, many cities now have excess office space that could potentially become residential housing.” Ultimately, Rollet hopes his research can influence urban policymakers to better serve city residents.
A happy accident
Rollet’s first exposure to economics was almost accidental. As a teenager, he stumbled upon the lecture videos of a game theory course at Yale University. “I randomly clicked on the available courses,” he said, “and I watched the videos, and I found it interesting.”
In high school and college, he focused on math and physics. “It’s the kind of training you’re typically pushed to do in France,” he says. But at the end of his first year at École Polytechnique — mandatory military training for all students — he remembered the Yale course that he had watched in high school. He had spent that year helping run a military service program for disadvantaged youth. “I was looking for an enjoyable way to start studying again,” he says. “So I went back to game theory.”
Rollet decided to take a game theory course with an economics professor, Pierre Boyer, who would play a key role in his academic path. Through conversations with Boyer, Rollet learned that economics could provide a rigorous, mathematical approach to understanding the topics around international development and international politics that had long fascinated him. Boyer introduced Rollet to two MIT-trained economists, professors Vincent Pons and Benjamin Marx, with whom he continues to collaborate today. A research visit to the U.S. in 2019 to work with them solidified his interest in pursuing graduate school. Shortly thereafter, he began his PhD at MIT.
Why cities get “stuck”
Rollet’s research explores why cities struggle to adapt their built environments as economic conditions shift, and why certain urban spaces become “stuck” in outdated patterns of development. He’s drawn to cities because they are a microcosm of different interacting systems in economics. “To understand cities, you need to understand how labor markets work, how the housing market works, and how transportation works,” he notes.
Rollet has spent most of his PhD focusing on New York City. By examining detailed data on building permits, real estate transactions, rents, and zoning changes, he has tracked the evolution of every building in the city over nearly two decades, studying when and why developers choose to demolish buildings and construct new ones, and how these decisions are influenced by economic, regulatory, and technological constraints. By combining computational theory and data — which often includes information on natural experiments (i.e., What happens when a city changes a regulation?) — Rollet aims to reveal generalizable principles underlying how cities grow and evolve.
Originally shaped as a manufacturing hub with dense commercial centers and sprawling residential outskirts, New York’s physical structure has been largely frozen since zoning regulations were imposed in the 1960s. Despite dramatic shifts in population and economic activity, the city’s regulations have barely budged, creating profound mismatches: soaring housing costs, overcrowded residential areas, and underutilized commercial spaces. The buildings are expensive to replace, and regulations are notoriously hard to change once they are established.
Rollet’s findings reveal critical inefficiencies. In cities like New York or Boston, housing often sells for hundreds of thousands of dollars more than it costs to build. This large gap suggests that demand far outpaces supply: There simply aren’t enough homes being built. “When the housing supply is too constrained, we are effectively wasting resources, making housing unnecessarily expensive,” he explains.
But implementing any kind of action or policy to alleviate these inefficiencies has downstream effects. For example, it can have different impacts on different groups of people. “There will be winners and losers,” Rollet explains. “One reason is that you might directly care about the welfare of a certain group, like directly providing housing for lower-income households. Another reason is that if there are sufficiently many people who are losers of a certain policy, or if they’re sufficiently powerful, they’re going to be able to block the policy change, and this poses a political constraint.”
So what makes a city “stuck”? “Much of the time,” Rollet says, “it’s policy.” But the effects of policy changes take time to materialize and might be difficult for people to detect. Rollet cites Cambridge’s recent zoning reform allowing the construction of six-story buildings as a case in point. “These policy changes can benefit a lot of people, by reducing the housing prices a bit for everyone,” he says, “but individual people won’t know it. This makes collective action very hard.”
Economics, however, provides a toolkit to characterize and quantify these effects. “What economists can bring to the table is to give policymakers more information on the likely consequences of their policy actions,” Rollet says.
Striving to “improve things”
As Rollet enters the home stretch of his PhD, he’s grateful to his advisors in the economics department for helping him develop a foundation for the diverse set of tools necessary for his work. From professors Dave Donaldson and David Atkin, he learned how to adapt methods traditionally used in the study of international trade, to analyze the movement of people across neighborhoods and cities. From Professor Tobias Salz, he gained insights into modeling the behavior of firms over time, which he now applies to understanding the actions of real estate developers. “The training here pushes you to produce research that truly stands out,“ he says. “The courses helped me discover a new set of fields and methods.”
Beyond research, Rollet actively contributes to his department, including serving as the co-president of the Graduate Economics Association. “MIT is truly the best place for economics, not just because of their courses, but because it’s a really friendly department where people help each other out,” he says. “The Graduate Economics Association helps to build that sense of community, and I wanted to be a part of that.” In addition, he is a member of a mental health and peer support group in the department.
Rollet also enjoys teaching. He has been a teaching assistant for microeconomics and international trade courses and has built an impressive writing repertoire explaining complex concepts in several fields. In high school, one of Rollet’s hobbies was writing quantum theory explainers on the internet for general audiences. Some publishers found his writing and contacted him about turning it into a book. The book was published, and has sold more than 14,000 copies. As a college student, Rollet worked on two books: one on game theory for general audiences, and an intro to economics textbook that two professors recruited him to co-author. It’s still the standard textbook at École Polytechnique today. “It was my Covid activity,” Rollet laughs.
Looking forward, Rollet aims to pursue a career in research and teaching. His immediate goal remains clear: develop research that meaningfully impacts policy, by shedding light on how cities can overcome constraints and evolve in ways that better serve their residents. He’s excited about how, in the future, more fine-grained and detailed data sources could shed light on how micro behavior can lead to macro outcomes.
"Housing and cities — these markets are failing in important ways in many parts of the world. There’s real potential for policy to improve things.”
MIT’s Mason Estrada to sign with the Los Angeles Dodgers
Like almost any MIT student, Mason Estrada wants to take what he learned on campus and apply it to the working world.
Unlike any other MIT student, Estrada will soon be going to work on a pitcher’s mound, and some day Dodger Stadium might be his office.
Estrada, the star pitcher for MIT’s baseball team, is signing a contract with the Los Angeles Dodgers organization, after the team selected him in the 7th round of the Major League Baseball draft on July 14. The right-hander, whose stellar stuff earned significant attention from MLB scouts, will be reporting soon to the Dodgers’ instructional camp in Arizona.
“I’m definitely excited,” says Estrada, who was projected as a likely draft pick but did not know he would be selected by the Dodgers, Major League Baseball’s defending champions.
From the outside, MIT might seem like an atypical starting point for a pitching career, but it has helped Estrada in multiple ways: by providing a strong baseball program in itself, and, more subtly, by reinforcing the value of systematic improvement, at a time when baseball pitching increasingly resembles, well, engineering.
On the first count, Estrada praises his MIT coaches and teammates for the baseball environment they have helped provide.
“It was really awesome,” Estrada says about playing baseball at the Institute. “I was surrounded by a bunch of guys that wanted to win. There was a great team culture of grinding and working hard.”
Meanwhile, pitching in professional baseball more than ever involves “pitch design” or “pitch shaping.” For a decade now, major-league teams have used high-speed cameras to determine which pitches work best. In turn, pitchers are often reverse-engineering parts of their arsenals, by starting with the desired outcome, then finding the combination of velocity and movement to stymie hitters.
Into this setting, enter Estrada, an MIT aeronautics and astronautics major — although, he makes clear, pitching at MIT has never involved transferring aerodynamic knowledge from the classroom to the mound. Rather, what counts is using feedback and analysis to get better.
“It’s not necessarily based on the subject I was studying,” Estrada says. “It’s learning to think like an engineer generally, learning to think through problems the right way, and finding the best solution.”
This season, Estrada went 6-0 with a 2.21 ERA for MIT, striking out 66 and allowing a paltry 22 hits in 40 2/3 innings on the season. There are additional numbers that hint at his potential: Estrada’s fastball has hit 96 miles per hour, and he throws two types of sliders, with velocity in the upper 80s while producing up to 2,700 rotations per minute, in line with big-league metrics.
On the mound, Estrada uses his lower body to generate significant drive toward the plate — “I have to rely on my strength,” he says. Pitchers who share elements of this approach include Spencer Strider of the Atlanta Braves, although, Estrada emphasizes, “Everybody at the professional level is different.”
MIT’s baseball coaches praise Estrada’s dedication to the sport.
“Mason’s work ethic is through the roof,” says Todd Carroll, MIT’s pitching coach and recruiting coordinator, now in his 13th season at the Institute. Carroll thinks Estrada’s fastball and sliders could translate well to the professional game. The forward drive of Estrada’s motion, Carroll also notes, means that when Estrada delivers a pitch, “It’s on a hitter quick.”
Carroll concurs that the engineering mindset on campus actively helps players improve over time.
“MIT students are problem-solvers,” he says. “MIT is a place where people can do that as well as anywhere in the world. When a pitcher here misses the strike zone, that’s a problem they want to solve.”
Inevitably, all the off-field work, analysis, and preparation, is designed to let Estrada simply be himself on the diamond. For athletes, some parts of the brain are best put on pause when competing.
“In games, I’m just focused on getting the hitter out,” Estrada says. “I’m staying in the moment.”
As it happens, baseball’s relatively new world of pitch shaping and pitch design has been enabled by MIT-linked technology. The kind of high-speed video camera many teams use, the Edgertronic, is manufactured by Sanstreak Corp., founded by Mike Matter ’84, a graduate of what is now the Department of Electrical Engineering and Computer Science. If the camera name sounds familiar, it should: Matter named it in homage to Harold “Doc” Edgerton, the legendary MIT pioneer of high-speed photography, whom Matter counted as a mentor.
Estrada is the fifth MIT undergraduate selected in baseball’s draft, which dates to 1966, and the highest-drafted player in MIT history at 225th overall. The others are Alan Dopfel ’72, selected by the California Angels; Jason Szuminski ’00, drafted by the San Diego Padres; Austin Filiere ’18, picked by the Chicago Cubs; and David Hesslink ’17, chosen by the Seattle Mariners. Of those players, Szuminski reached the majors, with the Padres.
At least two major-league pitchers also earned MIT degrees after finishing long baseball careers: Chris Capuano MBA ’19, a former All-Star with the Brewers, who received his master’s degree in management as part of the MIT Sloan Fellows program, and Skip Lockwood SM ’83.
As a Dodger, Estrada joins an organization famed for great pitching: Since the team moved to Los Angeles in 1958, their star pitchers have included Sandy Koufax, Don Drysdale, Fernando Valenzuela, Orel Hershiser, and Clayton Kershaw.
Beyond that, the Dodgers are known for investing considerable resources in player development, staying on the leading edge of analytics while bulking up their staff in order to help players improve. They have won the World Series twice this decade, in 2020 and 2024.
Whatever happens on the diamond, Estrada wants to return to MIT to complete his degree. Before the draft, he had made plans to temporarily transfer to the University of Tennessee to play Division I baseball next season, with the plan of returning to MIT as a student. However, Estrada will not be doing that now that he is signing with the Dodgers.
As things now stand, Estrada is taking a leave of absence from the Institute while his professional career starts to unfold.
“I just want to be clear I’m very thankful to MIT and to the MIT baseball staff for all they’ve done,” Estrada says.
And now, campus experience in hand, Estrada is off to his very distinctive work environment.
Security Vulnerabilities in ICEBlock
The ICEBlock tool has vulnerabilities:
The developer of ICEBlock, an iOS app for anonymously reporting sightings of US Immigration and Customs Enforcement (ICE) officials, promises that it “ensures user privacy by storing no personal data.” But that claim has come under scrutiny. ICEBlock creator Joshua Aaron has been accused of making false promises regarding user anonymity and privacy, being “misguided” about the privacy offered by iOS, and of being an Apple fanboy. The issue isn’t what ICEBlock stores. It’s about what it could accidentally reveal through its tight integration with iOS...
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New tool gives anyone the ability to train a robot
Teaching a robot new skills used to require coding expertise. But a new generation of robots could potentially learn from just about anyone.
Engineers are designing robotic helpers that can “learn from demonstration.” This more natural training strategy enables a person to lead a robot through a task, typically in one of three ways: via remote control, such as operating a joystick to remotely maneuver a robot; by physically moving the robot through the motions; or by performing the task themselves while the robot watches and mimics.
Learning-by-doing robots usually train in just one of these three demonstration approaches. But MIT engineers have now developed a three-in-one training interface that allows a robot to learn a task through any of the three training methods. The interface is in the form of a handheld, sensor-equipped tool that can attach to many common collaborative robotic arms. A person can use the attachment to teach a robot to carry out a task by remotely controlling the robot, physically manipulating it, or demonstrating the task themselves — whichever style they prefer or best suits the task at hand.
The MIT team tested the new tool, which they call a “versatile demonstration interface,” on a standard collaborative robotic arm. Volunteers with manufacturing expertise used the interface to perform two manual tasks that are commonly carried out on factory floors.
The researchers say the new interface offers increased training flexibility that could expand the type of users and “teachers” who interact with robots. It may also enable robots to learn a wider set of skills. For instance, a person could remotely train a robot to handle toxic substances, while further down the production line another person could physically move the robot through the motions of boxing up a product, and at the end of the line, someone else could use the attachment to draw a company logo as the robot watches and learns to do the same.
“We are trying to create highly intelligent and skilled teammates that can effectively work with humans to get complex work done,” says Mike Hagenow, a postdoc at MIT in the Department of Aeronautics and Astronautics. “We believe flexible demonstration tools can help far beyond the manufacturing floor, in other domains where we hope to see increased robot adoption, such as home or caregiving settings.”
Hagenow will present a paper detailing the new interface, at the IEEE Intelligent Robots and Systems (IROS) conference in October. The paper’s MIT co-authors are Dimosthenis Kontogiorgos, a postdoc at the MIT Computer Science and Artificial Intelligence Lab (CSAIL); Yanwei Wang PhD ’25, who recently earned a doctorate in electrical engineering and computer science; and Julie Shah, MIT professor and head of the Department of Aeronautics and Astronautics.
Training together
Shah’s group at MIT designs robots that can work alongside humans in the workplace, in hospitals, and at home. A main focus of her research is developing systems that enable people to teach robots new tasks or skills “on the job,” as it were. Such systems would, for instance, help a factory floor worker quickly and naturally adjust a robot’s maneuvers to improve its task in the moment, rather than pausing to reprogram the robot’s software from scratch — a skill that a worker may not necessarily have.
The team’s new work builds on an emerging strategy in robot learning called “learning from demonstration,” or LfD, in which robots are designed to be trained in more natural, intuitive ways. In looking through the LfD literature, Hagenow and Shah found LfD training methods developed so far fall generally into the three main categories of teleoperation, kinesthetic training, and natural teaching.
One training method may work better than the other two for a particular person or task. Shah and Hagenow wondered whether they could design a tool that combines all three methods to enable a robot to learn more tasks from more people.
“If we could bring together these three different ways someone might want to interact with a robot, it may bring benefits for different tasks and different people,” Hagenow says.
Tasks at hand
With that goal in mind, the team engineered a new versatile demonstration interface (VDI). The interface is a handheld attachment that can fit onto the arm of a typical collaborative robotic arm. The attachment is equipped with a camera and markers that track the tool’s position and movements over time, along with force sensors to measure the amount of pressure applied during a given task.
When the interface is attached to a robot, the entire robot can be controlled remotely, and the interface’s camera records the robot’s movements, which the robot can use as training data to learn the task on its own. Similarly, a person can physically move the robot through a task, with the interface attached. The VDI can also be detached and physically held by a person to perform the desired task. The camera records the VDI’s motions, which the robot can also use to mimic the task when the VBI is reattached.
To test the attachment’s usability, the team brought the interface, along with a collaborative robotic arm, to a local innovation center where manufacturing experts learn about and test technology that can improve factory-floor processes. The researchers set up an experiment where they asked volunteers at the center to use the robot and all three of the interface’s training methods to complete two common manufacturing tasks: press-fitting and molding. In press-fitting, the user trained the robot to press and fit pegs into holes, similar to many fastening tasks. For molding, a volunteer trained the robot to push and roll a rubbery, dough-like substance evenly around the surface of a center rod, similar to some thermomolding tasks.
For each of the two tasks, the volunteers were asked to use each of the three training methods, first teleoperating the robot using a joystick, then kinesthetically manipulating the robot, and finally, detaching the robot’s attachment and using it to “naturally” perform the task as the robot recorded the attachment’s force and movements.
The researchers found the volunteers generally preferred the natural method over teleoperation and kinesthetic training. The users, who were all experts in manufacturing, did offer scenarios in which each method might have advantages over the others. Teleoperation, for instance, may be preferable in training a robot to handle hazardous or toxic substances. Kinesthetic training could help workers adjust the positioning of a robot that is tasked with moving heavy packages. And natural teaching could be beneficial in demonstrating tasks that involve delicate and precise maneuvers.
“We imagine using our demonstration interface in flexible manufacturing environments where one robot might assist across a range of tasks that benefit from specific types of demonstrations,” says Hagenow, who plans to refine the attachment’s design based on user feedback and will use the new design to test robot learning. “We view this study as demonstrating how greater flexibility in collaborative robots can be achieved through interfaces that expand the ways that end-users interact with robots during teaching.”
This work was supported, in part, by the MIT Postdoctoral Fellowship Program for Engineering Excellence and the Wallenberg Foundation Postdoctoral Research Fellowship.