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New method enables robots to map a scene, identify objects in order to complete a set of tasks

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New method enables robots to map a scene, identify objects in order to complete a set of tasks


Helping robots zero in on the objects that matter
MIT’s Clio runs in real-time to map task-relevant objects in a robot’s surroundings, allowing the bot (Boston Dynamic’s quadruped robot Spot, pictured) carry out a natural language task (“pick up orange backpack”). Credit: Massachusetts Institute of Technology

Imagine having to straighten up a messy kitchen, starting with a counter littered with sauce packets. If your goal is to wipe the counter clean, you might sweep up the packets as a group. If, however, you wanted to first pick out the mustard packets before throwing the rest away, you would sort more discriminately, by sauce type. And if, among the mustards, you had a hankering for Grey Poupon, finding this specific brand would entail a more careful search.

MIT engineers have developed a method that enables robots to make similarly intuitive, task-relevant decisions.

The team’s new approach, named Clio, enables a robot to identify the parts of a scene that matter, given the tasks at hand. With Clio, a robot takes in a list of tasks described in natural language and, based on those tasks, it then determines the level of granularity required to interpret its surroundings and “remember” only the parts of a scene that are relevant.

In real experiments ranging from a cluttered cubicle to a five-story building on MIT’s campus, the team used Clio to automatically segment a scene at different levels of granularity, based on a set of tasks specified in natural-language prompts such as “move rack of magazines” and “get first aid kit.”

The team also ran Clio in real-time on a quadruped robot. As the robot explored an office building, Clio identified and mapped only those parts of the scene that related to the robot’s tasks (such as retrieving a dog toy while ignoring piles of office supplies), allowing the robot to grasp the objects of interest.

Clio is named after the Greek muse of history, for its ability to identify and remember only the elements that matter for a given task. The researchers envision that Clio would be useful in many situations and environments in which a robot would have to quickly survey and make sense of its surroundings in the context of its given task.

“Search and rescue is the motivating application for this work, but Clio can also power domestic robots and robots working on a factory floor alongside humans,” says Luca Carlone, associate professor in MIT’s Department of Aeronautics and Astronautics (AeroAstro), principal investigator in the Laboratory for Information and Decision Systems (LIDS), and director of the MIT SPARK Laboratory. “It’s really about helping the robot understand the environment and what it has to remember in order to carry out its mission.”

The team details their results in a study published today in the journal IEEE Robotics and Automation Letters. Carlone’s co-authors include members of the SPARK Lab: Dominic Maggio, Yun Chang, Nathan Hughes, and Lukas Schmid; and members of MIT Lincoln Laboratory: Matthew Trang, Dan Griffith, Carlyn Dougherty, and Eric Cristofalo.

Open fields

Huge advances in the fields of computer vision and natural language processing have enabled robots to identify objects in their surroundings. But until recently, robots were only able to do so in “closed-set” scenarios, where they are programmed to work in a carefully curated and controlled environment, with a finite number of objects that the robot has been pretrained to recognize.

In recent years, researchers have taken a more “open” approach to enable robots to recognize objects in more realistic settings. In the field of open-set recognition, researchers have leveraged deep-learning tools to build neural networks that can process billions of images from the internet, along with each image’s associated text (such as a friend’s Facebook picture of a dog, captioned “Meet my new puppy!”).

From millions of image-text pairs, a neural network learns from, then identifies, those segments in a scene that are characteristic of certain terms, such as a dog. A robot can then apply that neural network to spot a dog in a totally new scene.

But a challenge still remains as to how to parse a scene in a useful way that is relevant for a particular task.

“Typical methods will pick some arbitrary, fixed level of granularity for determining how to fuse segments of a scene into what you can consider as one ‘object,'” Maggio says. “However, the granularity of what you call an ‘object’ is actually related to what the robot has to do. If that granularity is fixed without considering the tasks, then the robot may end up with a map that isn’t useful for its tasks.”

Information bottleneck

With Clio, the MIT team aimed to enable robots to interpret their surroundings with a level of granularity that can be automatically tuned to the tasks at hand.

For instance, given a task of moving a stack of books to a shelf, the robot should be able to determine that the entire stack of books is the task-relevant object. Likewise, if the task were to move only the green book from the rest of the stack, the robot should distinguish the green book as a single target object and disregard the rest of the scene—including the other books in the stack.

The team’s approach combines state-of-the-art computer vision and large language models comprising neural networks that make connections among millions of open-source images and semantic text. They also incorporate mapping tools that automatically split an image into many small segments, which can be fed into the neural network to determine if certain segments are semantically similar.

The researchers then leverage an idea from classic information theory called the “information bottleneck,” which they use to compress a number of image segments in a way that picks out and stores segments that are semantically most relevant to a given task.

“For example, say there is a pile of books in the scene and my task is just to get the green book. In that case, we push all this information about the scene through this bottleneck and end up with a cluster of segments that represent the green book,” Maggio explains.

“All the other segments that are not relevant just get grouped in a cluster which we can simply remove. And we’re left with an object at the right granularity that is needed to support my task.”

The researchers demonstrated Clio in different real-world environments.

“What we thought would be a really no-nonsense experiment would be to run Clio in my apartment, where I didn’t do any cleaning beforehand,” Maggio says.

The team drew up a list of natural-language tasks, such as “move pile of clothes” and then applied Clio to images of Maggio’s cluttered apartment. In these cases, Clio was able to quickly segment scenes of the apartment and feed the segments through the Information Bottleneck algorithm to identify those segments that made up the pile of clothes.

They also ran Clio on Boston Dynamic’s quadruped robot, Spot. They gave the robot a list of tasks to complete, and as the robot explored and mapped the inside of an office building, Clio ran in real-time on an on-board computer mounted to Spot, to pick out segments in the mapped scenes that visually relate to the given task.

The method generated an overlaying map showing just the target objects, which the robot then used to approach the identified objects and physically complete the task.

“Running Clio in real-time was a big accomplishment for the team,” Maggio says. “A lot of prior work can take several hours to run.”

Going forward, the team plans to adapt Clio to be able to handle higher-level tasks and build upon recent advances in photorealistic visual scene representations.

“We’re still giving Clio tasks that are somewhat specific, like ‘find a deck of cards,'” Maggio says. “For search and rescue, you need to give it more high-level tasks, like ‘find survivors,’ or ‘get power back on.’ So, we want to get to a more human-level understanding of how to accomplish more complex tasks.”

More information:
Dominic Maggio et al, Clio: Real-Time Task-Driven Open-Set 3D Scene Graphs, IEEE Robotics and Automation Letters (2024). DOI: 10.1109/LRA.2024.3451395. dspace.mit.edu/handle/1721.1/157072

This story is republished courtesy of MIT News (web.mit.edu/newsoffice/), a popular site that covers news about MIT research, innovation and teaching.

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New method enables robots to map a scene, identify objects in order to complete a set of tasks (2024, September 30)
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from https://techxplore.com/news/2024-09-method-enables-robots-scene-tasks.html

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New insights into exotic nuclei creation using Langevin equation model

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New insights into exotic nuclei creation using Langevin equation model


New insights into exotic nuclei creation
Evolution of nuclear system in fusion and MNT reactions. MNT reactions encompass quasi-elastic (QE), deep inelastic (DI), and quasi-fission (QF) processes. Understanding the complex mechanisms involved in MNT reactions presents significant challenges for theoretical investigations. Credit: Minghao Zhang

Researchers have introduced a model based on the Langevin equation that offers new insights into the formation of exotic nuclei. This development could enhance the ability to produce rare isotopes that are valuable for various applications in science and medicine.

The study is published in the journal Nuclear Science and Techniques.

A research team led by Professor Feng-Shou Zhang has developed and applied this model to study multinucleon transfer (MNT) processes in heavy-ion collisions. The model provides a more precise understanding of energy dissipation during heavy-ion collisions, which is important for predicting nuclear reaction outcomes. Simulations of nuclear reactions, such as 40Ar + 232Th, 136Xe + 238U, and 136Xe + 209Bi, have shown that the model’s predictions of cross-sections and angular distributions are in good agreement with experimental results.

Modeling nuclear reactions, particularly those involved in producing exotic nuclei, is challenging due to their complexity. Conventional methods like projectile fragmentation and fusion-evaporation have limitations, particularly in synthesizing new transuranium and superheavy elements.

This model addresses these challenges by simplifying the process, reducing the number of adjustable parameters, and focusing on key physical processes. It successfully simulates energy and scattering angle distributions, offering insights into deep inelastic and quasi-fission processes.

  • New insights into exotic nuclei creation
    A simulated trajectory for the 40Ar + 232Th collision at Elab = 388 MeV. The trajectory and its projections of the evolution of total kinetic energy (TKE), elongation, and mass of heavier nucleus are illustrated. For each impact parameter, 500 trajectories have been simulated. Credit: Ying Zou
  • New insights into exotic nuclei creation
    Profile of the trajectory in Fig.2 at the indicated time. The Langevin equation model, as a phenomenological approach, simulates nuclear reactions by solving for the evolution of collective coordinates. The system’s shape evolution depicted in the figure illustrates the collective coordinates during the simulation. Credit: Ying Zou
  • New insights into exotic nuclei creation
    Center-of-mass angular distribution of the damped cross section for events with TKE within the indicated range in the 136Xe + 209Bi reaction at Elab = 1130 MeV. Histogram is the calculation. Credit: Ying Zou

The improved accuracy of MNT reaction predictions provided by this model could facilitate the production of isotopes that are difficult to generate using other methods. These isotopes are valuable for scientific research and medical applications, such as diagnostics and treatments. According to Prof. Zhang, the goal is to keep the model comprehensive yet practical for experimental use.

This development represents a step forward in nuclear physics, contributing to the understanding of exotic nuclei production through MNT reactions. Further refinement of the model may enhance its utility in guiding future research and improving rare isotope production processes.

This research was conducted in collaboration with Beijing Normal University, Beijing Academy of Science and Technology, and the National Laboratory of Heavy Ion Accelerator of Lanzhou.

More information:
Ying Zou et al, Investigation of multinucleon transfer processes in the Langevin equation model, Nuclear Science and Techniques (2024). DOI: 10.1007/s41365-024-01557-4

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New insights into exotic nuclei creation using Langevin equation model (2024, September 30)
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Study warns of $557 trillion in stranded assets by 2050 if fossil fuel investments continue

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Study warns of 7 trillion in stranded assets by 2050 if fossil fuel investments continue


Vast 'stranded assets' if world continues investing in polluting industries
Graphical representation of the steps to create the capital stock portfolio. Data sources are shown in italics. (1) World Bank Wealth Accounts and Penn World Tables 10. (2) ONS, Statistics Canada, and Statistics Netherlands. (3) OECD Economic Outlook database. Where this is unavailable, average growth rates from the World Bank Wealth Accounts are used. (4) Covers 1980–2026. Extrapolated to 2030. Credit: Environmental Research: Climate (2024). DOI: 10.1088/2752-5295/ad7313

Continued investment in carbon-intensive industries will drastically increase the amount of “stranded assets” as the world moves to net-zero emissions, researchers warn.

The study assesses how much capital—the value of physical assets like buildings and, uniquely in this study, the value of workers—could be stranded (losing its value) if the world reaches net zero emissions in 2050.

The paper, published in the journal Environmental Research: Climate is titled “Stranded human and produced capital in a net-zero transition.

Stranded assets could include a worker losing their job and future income as their industry declines, or a coal power station losing value as renewables take over.

The study—by Exeter and Lancaster universities—compares two scenarios to investigate how delaying the transition could affect the total capital value at risk accumulated by 2050: one where the world completely stopped investing in carbon-intensive industries in 2020, and another where this is delayed to 2030.

A complete switch-off from fossil fuel investment in 2020 would have left $117 trillion of global capital at risk—while delaying to 2030 raises this to $557 trillion (37% of total global capital today).

While these are the maximum possible figures—and they could be reduced by retraining workers and retrofitting assets—they highlight the vast economic risks from continued investment in declining industries.

“The longer we wait, the more disorderly the transition will be,” said Cormac Lynch, from the University of Exeter. “An orderly transition would place communities in a good position to take advantage of new opportunities as the economy changes—while a disorderly one could put some areas at risk of post-industrial decline.”

Asked if the findings could support calls to delay or abandon net-zero policies, Daniel Chester from Lancaster University said, “The impacts of climate change itself are likely to be far more costly. And parts of the transition are happening already. For example, renewables like solar PV are already at cost-parity with fossil fuel equivalents, and electric vehicles are not far behind.

“What our research shows is that it makes practical sense, not just ethical sense, to embrace the transition now rather than resist it. Instead of delaying the transition, policymakers should be transforming educational and financial systems—creating new opportunities, especially in regions dependent on fossil-fuel industries—to ensure communities are not left behind.”

The world must now cut carbon emissions at an unprecedented rate to meet the goals of the Paris Agreement, thereby limiting the worst effects of climate change.

This will inevitably create new economic opportunities but will also threaten the value of some existing occupations and physical assets, investments in which have been called a “carbon bubble.”

The researchers collated available data to estimate the makeup of the global stock of capital assets and their economic lifespans.

They then simulated the early retirement of these capital assets (e.g. buildings decommissioned earlier than expected or workers being made unemployed) necessary to achieve the net zero targets set by governments, comparing these outcomes to scenarios where they are allowed to retire at the end of their normal working life.

More information:
Daniel Chester et al, Stranded human and produced capital in a net-zero transition, Environmental Research: Climate (2024). DOI: 10.1088/2752-5295/ad7313

Citation:
Study warns of $557 trillion in stranded assets by 2050 if fossil fuel investments continue (2024, September 30)
retrieved 30 September 2024
from https://techxplore.com/news/2024-09-trillion-stranded-assets-fossil-fuel.html

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Researchers urge governments to enlist emotion when fighting fake news

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Researchers urge governments to enlist emotion when fighting fake news


fake news
Credit: Pixabay/CC0 Public Domain

Real people with relatable stories can help public agencies counter social media disinformation campaigns and “fake news” around issues such as vaccination programs, academic researchers say.

They examined how Laura Brennan, a 25-year-old woman who had been diagnosed with terminal cervical cancer, used her scientifically informed yet emotionally charged social media posts to significantly shift public perceptions of Ireland’s HPV vaccination program. Her compelling personal story countered the aggressive anti-vaccine rhetoric and led to a positive turnaround in public opinion.

She worked closely with the Irish Health Service Executive (IHSE), who supported her and provided her with facts and insights into both the vaccine and cervical cancer.

Dr. Itziar Castello, Reader in Corporate Social Responsibility at Bayes Business School, City St George’s University of London, and colleagues from ESSCA and Surrey universities, concluded that the “emotional legitimacy” provided by people with real life experience of the issue can be “transferred” to the public body involved.

Laura approached the IHSE in 2015 to discuss misleading social media posts promoting scare stories claiming young people had developed serious illnesses after receiving the HPV vaccine. The vaccine is offered to adolescents in both Ireland and the UK to protect against the human papillomavirus (HPV), which can cause cervical cancer.

Deploying emotional intelligence

In the paper, which has been published in Business & Society, the academics note that the anti-vaxxers’ misinformation campaign had driven Irish HPV vaccination rates down from 85% to 50% in less than two years. A counter-campaign by the IHSE “based on logic and facts had limited success in boosting vaccination uptake.”

While governments and other public bodies have worked with external partners to combat fake news, often spread by social media, this is largely confined to fact-checking or verification of official data. Previous research, the paper suggests, has not tackled misinformation aimed at attacking an organization’s “legitimacy” and the role emotion plays in concert with science in responses to such attacks.

Dr. Castello said, “The case study analysis shows the importance of emotional intelligence—of not just relying on facts and science but using emotions to take on and expose fake news. People remember how you make them feel and often that memory is stronger than their recall of facts and figures.

“That approach could have been applied to the recent riots in the UK and should be considered as the NHS rolls out the autumn COVID and flu vaccination programs. We know that misinformation has undermined vaccination campaigns ranging from MMR to shingles, COVID and flu.”

Laura’s involvement, initially as a patient advocate and then as the public face of the IHSE’s HPV campaigns, proved a turning point in the battle against the anti-vaxxers.

With extensive support from the IHSE, Laura (pictured above) raised public awareness of the vaccination program and challenged anti-vaxxer propaganda. This involved using “emotional batteries”—a metaphor used to describe how “emotional energy” is generated through positive and negative emotions sparked by first-hand accounts, mostly through social media posts.

She posted images and videos of both emotional moments involving her treatment and life-limiting diagnosis and ‘relatable’ footage of herself in the pub with friends having a normal night out.

The paper says, “Her capacity to emotionally connect with the public through social and mass media was decisive in boosting Ireland’s HPV vaccination rates to 74%.”

Co-author Dr. Marie Joachim, who teaches at the ESSCA School of Management in France, explains, “It is crucial that public institutions acknowledge emotions in their response to fake news. They need to rely on third parties like Laura to emotionally connect with the public and, in the end, regain legitimacy.”

However, the case study emphasizes the importance of the IHSE’s close and supportive relationship with Laura—ensuring she had the knowledge and confidence to forcefully rebut social media posts.

More information:
Marie Joachim et al, Moving Beyond “Facts Are Facts”: Managing Emotions and Legitimacy After a Fake News Attack, Business & Society (2024). DOI: 10.1177/00076503241281632

Citation:
Researchers urge governments to enlist emotion when fighting fake news (2024, September 30)
retrieved 30 September 2024
from https://phys.org/news/2024-09-urge-emotion-fake-news.html

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Satellite service DirecTV buys rival Dish as it fights the onslaught of streaming services

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Satellite service DirecTV buys rival Dish as it fights the onslaught of streaming services


Satellite service DirecTV buys rival Dish as it fights the onslaught of streaming services
In this Feb. 23, 2011, file photo, Dish Network satellite dishes are shown at an apartment complex in Palo Alto, Calif. Credit: AP Photo/Paul Sakuma, File

DirecTV is buying Dish and Sling, a deal it has sought to complete for years, as the company seeks to better compete against streaming services that have become dominant.

DirecTV said Monday that it will acquire Dish TV and Sling TV from its owner EchoStar in a debt exchange transaction that includes a payment of $1, plus the assumption of approximately $9.8 billion in debt.

The prospect of a DirecTV-Dish combo has long been rumored, with headlines about reported talks popping up over the years. And the two almost merged more than two decades ago—but the Federal Communications Commission blocked their owners’ then-$18.5 billion deal, citing antitrust concerns.

The pay-for-TV market has shifted significantly since. As more and more consumers tune into online streaming giants, demand for more traditional satellite continues to shrink. And, although high-profile acquisitions have proven to be particularly tough under the Biden-Harris administration, that may make regulators more inclined to approve DirecTV and Dish’s pairing this time around.

DirecTV said Monday that the transaction will help it bring smaller content packages to consumer at lower prices and essentially provide a one-stop shopping experience for entertainment programming.

It’s hoping this will appeal to those who have left satellite video services for streaming. The company said that combined, DirecTV and Dish have collectively lost 63% of their satellite customers since 2016.

“DirecTV operates in a highly competitive video distribution industry,” DirecTV CEO Bill Morrow said in a statement. “With greater scale, we expect a combined DirecTV and Dish will be better able to work with programmers to realize our vision for the future of tv, which is to aggregate, curate, and distribute content tailored to customers’ interests, and to be better positioned to realize operating efficiencies while creating value for customers through additional investment.”

Satellite service DirecTV buys rival Dish as it fights the onslaught of streaming services
A DirectTV logo identifies the company’s headquarters in Caracas, Venezuela, Friday, May 22, 2020. Credit: AP Photo/Ariana Cubillos, File

The current deal could provide a key lifeline for EchoStar. The Colorado-based telecommunications company has reportedly faced the prospect of bankruptcy as it continues to burn through cash and see losses pile up.

In a recent securities filing, EchoStar disclosed that it had just $521 million in “cash on hand.” And the company forecast negative cash flows for the remainder of the year—while also pointing to major looming debt payments, with more than $1.98 billion of debt set to mature in November.

“With an improved financial profile, we will be better positioned to continue enhancing and deploying our nationwide 5G Open RAN wireless network,” EchoStar President and CEO Hamid Akhavan said. “This will provide U.S. wireless consumers with more choices and help to drive innovation at a faster pace.”

By shedding Dish, EchoStar will be able to focus its efforts elsewhere, like its wireless carrier Boost Mobile.

“We are playing to win in the wireless business. there’s no doubt about it,” Akhavan said during a conference call, adding that the company may need to seek additional funding and financing in the future to achieve its goals.

Shares of EchoStar fell more than 14% in Monday midday trading.

The DirecTV and Dish deal is targeted to close in 2025’s fourth quarter. But it is contingent on several factors, including regulatory approvals and bondholders writing off nearly $1.6 billion in debt related to Dish.

Satellite service DirecTV buys rival Dish as it fights the onslaught of streaming services
An AT&T sign is seen at a store in Pittsburgh, Monday, Jan. 30, 2023. Credit: AP Photo/Gene J. Puskar, File, File

The combined company will be based in El Segundo, California.

“We believe regulatory approval is likely to be greater than 50% given the opportunity for the combined company to improve its competitiveness to offer a range of linear video packages as well as to take a more aggressive stance on offering a live streaming video product,” Michael Rollins of Citi Investment Research wrote in a note to clients.

But the analyst added that there’s still significant uncertainty related to whether or not the Federal Communications Commission, Department of Justice and other possible regulators give the necessary approvals, based on previous talks with company management and industry experts over the last few years.

Shortly before DirecTV made its announcement, AT&T said it was selling its remaining stake in DirecTV to private equity firm TPG in a deal valued at about $7.6 billion.

The move ends the communication giant’s remaining ties to the entertainment industry.

AT&T said Monday in a filing with the Securities and Exchange Commission that it will receive payments from TPG and DirecTV for its remaining 70% stake in the satellite TV company. This includes $1.7 billion in the second half of the year and $5.4 billion next year. The remaining amount will be paid in 2029.

AT&T purchased DirectTV for $48.5 billion back in 2015. But in 2021, following the loss of millions of customers, AT&T sold a 30% stake of the business to TPG for $16.25 billion.

AT&T’s deal is expected to close in the second half of 2025.

© 2024 The Associated Press. All rights reserved. This material may not be published, broadcast, rewritten or redistributed without permission.

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Satellite service DirecTV buys rival Dish as it fights the onslaught of streaming services (2024, September 30)
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