Electromagnetic radiation leaking from the cable between your computer and monitor can be intercepted and decoded by AI to reveal what you are looking at

Between 2005 and 2021, Facebook, Twitter and YouTube were more likely to make policy changes in the weeks after negative stories in the media

A robot mimics the clever fin-folding mechanism used by tuna fish, which increased the bot's turning velocity by almost 33 per cent

To address the problem of AIs generating inaccurate information, a team of ethicists says there should be legal obligations for companies to reduce the risk of errors, but there are doubts about whether it would work

A newly identified smartphone vulnerability can reveal the floor plans of where you are and what you are doing - and it is possible that companies or intelligence agencies are already making use of it

Plans to create an interactive AI model of the legendary code breaker Alan Turing are reckless and problematic, says Matthew Sparkes

After their initial training phase, AI algorithms can’t update and learn from new data, meaning tech companies have to keep training new models from scratch

The US military has prioritised deploying high-altitude balloons that can carry out surveillance

A new procedure turns an alloy of nickel and titanium into a material as strong as steel but 20 times stretchier – and one application could be building planes with shape-shifting wings

Google has built a quantum computer that makes fewer errors as it is scaled up, and this may pave the way for machines that could solve useful real-world problems for the first time

The author of Sapiens has turned his attention to the information networks that shape our societies, but when you stop and think about what he's saying, it's obvious

Information on faces recognised, voice commands and internet searches can be extracted from an Amazon Echo smart assistant without help from the user or manufacturer

Are humanoid robots the future of space exploration? New Scientist reporter James Woodford took NASA's Valkyrie for a spin to find out

NASA’s Valkyrie is undergoing tests to understand what it would take to get a humanoid robot onto offshore facilities or into space. New Scientist's James Woodford took the controls to see what it is capable of

Experiments show that viewers can usually identify video deepfakes of famous politicians – but fake audio and text are harder to detect

An artificial intelligence model that can identify the calls of eight whale species is helping researchers track the elusive whale behind a perplexing sound in the Pacific

Artificial intelligence has more in common with ants than humans, says Neil Lawrence. Only by taking a more nuanced view of intelligence can we see how machines will truly transform society

It has become trivially easy to use artificial intelligence to edit images or generate video to remove unwanted objects or beautify scenes, but doing so leads to people misremembering what they have seen

Voice assistants can build profiles of their users’ habits and preferences, but the consistency and accuracy of these profiles vary

A US standards agency has issued new guidance saying organisations shouldn’t require users to change their passwords periodically – advice that is backed up by decades of research

The UK government's decision to return the Chagos Islands to Mauritius surprisingly threatens the extinction of millions of website addresses ending in ".io", and no one is quite sure what will happen next

While quantum computers are still in their infancy, more and more people are training to become quantum software developers

Google’s NotebookLM tool is billed as an AI-powered research assistant and can even turn your text history into a jovial fake podcast. But it could also tempt you into narcissism and nostalgia, says Jacob Aron

What happens if AI is trained to write choral music by feeding it a specially created vocal dataset? Moving new exhibition The Call tackles some thorny questions about AI and creativity – and stirs the soul with music

Large language models can be used to scam humans, but AI is also susceptible to being scammed – and some models are more gullible than others

Thanks to artificial intelligence, understanding animals may be closer than we think. But we may not like what they are going to tell us, says RSPCA chief executive Chris Sherwood

An off-the-shelf millimetre wave sensor can pick out the tiny vibrations made by a smartphone's speaker, enabling an AI model to transcribe the conversation, even at a distance in a noisy room

I have a confession to make. After taking a handful of autonomous taxi rides, I have gone from a hater to a friend of robot cars in just a few weeks, says Annalee Newitz

Four-legged robot dogs learned to perform new tricks by practising in a virtual platform that mimics real-world obstacles – a possible shortcut for training robots faster and more accurately

The controversies surrounding football’s video assistant referee (VAR) system highlight our troubled relationship with uncertainty – and point to potential solutions

Tigerair has again cancelled flights in and out of Denpasar, and there is no sign of the dispute being resolved.

Michael Chamberlain, who has died at 72, will be farewelled at Cooranbong, on the NSW Central Coast.

Only one Australian restaurant made the cut this year in the contentious World’s 50 Best Restaurants list.

We seem to be in the final stage of the apartment bubble, with developers offering huge inventives to Chinese agents.

After seven years of voicing Elena Ferrante’s ambitious heroine, the Italian actress brings Lenù Greco home.

Treat yourself to a Becky Lynch book signing, games with the Dropout stars, Kevin Smith’s Dogma, and so much more!

The Francis Ford Coppola film is now available to rentalopolis.

“Somehow, I couldn’t sing a rock song at the Rock Hall of Fame when I’m being inducted? It doesn’t make any sense to me, and it sticks in my craw.”

It’s the second-shortest book to be awarded the prize.

Can we trust whatever is going on with Becky Minkoff?

The finale doesn’t look to provide a definitive answer to what drove Aaron’s actions, much to the show’s credit.

Joe Marler discussed his recent comments about the Haka, which sparked backlash.

There has been another shock at the Grand Slam of Darts.

Emma Raducanu struck a deal to return to one of her favourite tournaments.

In the 1960s and 1970s, NASA spent a lot of time thinking about whether toroidal (donut-shaped) fuel tanks were the way to go with its spacecraft. Toroidal tanks have a bunch of potential advantages over conventional spherical fuel tanks. For example, you can fit nearly 40% more volume within a toroidal tank than if you were using multiple spherical tanks within the same space. And perhaps most interestingly, you can shove stuff (like the back of an engine) through the middle of a toroidal tank, which could lead to some substantial efficiency gains if the tanks could also handle structural loads.

Because of their relatively complex shape, toroidal tanks are much more difficult to make than spherical tanks. Even though these tanks can perform better, NASA simply doesn’t have the expertise to manufacture them anymore, since each one has to be hand-built by highly skilled humans. But a company called Machina Labs thinks that they can do this with robots instead. And their vision is to completely change how we make things out of metal.

The fundamental problem that Machina Labs is trying to solve is that if you want to build parts out of metal efficiently at scale, it’s a slow process. Large metal parts need their own custom dies, which are very expensive one-offs that are about as inflexible as it’s possible to get, and then entire factories are built around these parts. It’s a huge investment, which means that it doesn’t matter if you find some new geometry or technique or material or market, because you have to justify that enormous up-front cost by making as much of the original thing as you possibly can, stifling the potential for rapid and flexible innovation.

On the other end of the spectrum you have the also very slow and expensive process of making metal parts one at a time by hand. A few hundred years ago, this was the only way of making metal parts: skilled metalworkers using hand tools for months to make things like armor and weapons. The nice thing about an expert metalworker is that they can use their skills and experience to make anything at all, which is where Machina Labs’ vision comes from, explains CEO Edward Mehr who co-founded Machina Labs after spending time at SpaceX followed by leading the 3D printing team at Relativity Space.

“Craftsmen can pick up different tools and apply them creatively to metal to do all kinds of different things. One day they can pick up a hammer and form a shield out of a sheet of metal,” says Mehr. “Next, they pick up the same hammer, and create a sword out of a metal rod. They’re very flexible.”

The technique that a human metalworker uses to shape metal is called forging, which preserves the grain flow of the metal as it’s worked. Casting, stamping, or milling metal (which are all ways of automating metal part production) are simply not as strong or as durable as parts that are forged, which can be an important differentiator for (say) things that have to go into space. But more on that in a bit.

The problem with human metalworkers is that the throughput is bad—humans are slow, and highly skilled humans in particular don’t scale well. For Mehr and Machina Labs, this is where the robots come in.

“We want to automate and scale using a platform called the ‘robotic craftsman.’ Our core enablers are robots that give us the kinematics of a human craftsman, and artificial intelligence that gives us control over the process,” Mehr says. “The concept is that we can do any process that a human craftsman can do, and actually some that humans can’t do because we can apply more force with better accuracy.”

This flexibility that robot metalworkers offer also enables the crafting of bespoke parts that would be impractical to make in any other way. These include toroidal (donut-shaped) fuel tanks that NASA has had its eye on for the last half century or so.

Machina Labs’ CEO Edward Mehr (on right) stands behind a 15 foot toroidal fuel tank.Machina Labs

“The main challenge of these tanks is that the geometry is complex,” Mehr says. “Sixty years ago, NASA was bump-forming them with very skilled craftspeople, but a lot of them aren’t around anymore.” Mehr explains that the only other way to get that geometry is with dies, but for NASA, getting a die made for a fuel tank that’s necessarily been customized for one single spacecraft would be pretty much impossible to justify. “So one of the main reasons we’re not using toroidal tanks is because it’s just hard to make them.”

Machina Labs is now making toroidal tanks for NASA. For the moment, the robots are just doing the shaping, which is the tough part. Humans then weld the pieces together. But there’s no reason why the robots couldn’t do the entire process end-to-end and even more efficiently. Currently, they’re doing it the “human” way based on existing plans from NASA. “In the future,” Mehr tells us, “we can actually form these tanks in one or two pieces. That’s the next area that we’re exploring with NASA—how can we do things differently now that we don’t need to design around human ergonomics?”

Machina Labs’ ‘robotic craftsmen’ work in pairs to shape sheet metal, with one robot on each side of the sheet. The robots align their tools slightly offset from each other with the metal between them such that as the robots move across the sheet, it bends between the tools. Machina Labs

The video above shows Machina’s robots working on a tank that’s 4.572 m (15 feet) in diameter, likely destined for the Moon. “The main application is for lunar landers,” says Mehr. “The toroidal tanks bring the center of gravity of the vehicle lower than what you would have with spherical or pill-shaped tanks.”

Training these robots to work metal like this is done primarily through physics-based simulations that Machina developed in house (existing software being too slow), followed by human-guided iterations based on the resulting real-world data. The way that metal moves under pressure can be simulated pretty well, and although there’s certainly still a sim-to-real gap (simulating how the robot’s tool adheres to the surface of the material is particularly tricky), the robots are collecting so much empirical data that Machina is making substantial progress towards full autonomy, and even finding ways to improve the process.

An example of the kind of complex metal parts that Machina’s robots are able to make.Machina Labs

Ultimately, Machina wants to use robots to produce all kinds of metal parts. On the commercial side, they’re exploring things like car body panels, offering the option to change how your car looks in geometry rather than just color. The requirement for a couple of beefy robots to make this work means that roboforming is unlikely to become as pervasive as 3D printing, but the broader concept is the same: making physical objects a software problem rather than a hardware problem to enable customization at scale.

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.

ICRA@40: 23–26 September 2024, ROTTERDAM, NETHERLANDS

IROS 2024: 14–18 October 2024, ABU DHABI, UAE

ICSR 2024: 23–26 October 2024, ODENSE, DENMARK

Cybathlon 2024: 25–27 October 2024, ZURICH

Enjoy today’s videos!

Researchers at the Max Planck Institute for Intelligent Systems and ETH Zurich have developed a robotic leg with artificial muscles. Inspired by living creatures, it jumps across different terrains in an agile and energy-efficient manner.

[ Nature ] via [ MPI ]

Thanks, Toshi!

ETH Zurich researchers have now developed a fast robotic printing process for earth-based materials that does not require cement. In what is known as “impact printing,” a robot shoots material from above, gradually building a wall. On impact, the parts bond together, and very minimal additives are required.

[ ETH Zurich ]

How could you not be excited to see this happen for real?

[ arXiv paper ]

Can we all agree that sanding, grinding, deburring, and polishing tasks are really best done by robots, for the most part?

[ Cohesive Robotics ]

Thanks, David!

Using doors is a longstanding challenge in robotics and is of significant practical interest in giving robots greater access to human-centric spaces. The task is challenging due to the need for online adaptation to varying door properties and precise control in manipulating the door panel and navigating through the confined doorway. To address this, we propose a learning-based controller for a legged manipulator to open and traverse through doors.

[ arXiv paper ]

Isaac is the first robot assistant that’s built for the home. And we’re shipping it in fall of 2025.

Fall of 2025 is a long enough time from now that I’m not even going to speculate about it.

[ Weave Robotics ]

By patterning liquid metal paste onto a soft sheet of silicone or acrylic foam tape, we developed stretchable versions of conventional rigid circuits (like Arduinos). Our soft circuits can be stretched to over 300% strain (over 4x their length) and are integrated into active soft robots.

[ Science Robotics ] via [ Yale ]

NASA’s Curiosity rover is exploring a scientifically exciting area on Mars, but communicating with the mission team on Earth has recently been a challenge due to both the current season and the surrounding terrain. In this Mars Report, Curiosity engineer Reidar Larsen takes you inside the uplink room where the team talks to the rover.

[ NASA ]

I love this and want to burn it with fire.

[ Carpentopod ]

Very often, people ask us what Reachy 2 is capable of, which is why we’re showing you the manipulation possibilities (through teleoperation) of our technology. The robot shown in this video is the Beta version of Reachy 2, our new robot coming very soon!

[ Pollen Robotics ]

The Scalable Autonomous Robots (ScalAR) Lab is an interdisciplinary lab focused on fundamental research problems in robotics that lie at the intersection of robotics, nonlinear dynamical systems theory, and uncertainty.

[ ScalAR Lab ]

Astorino is a 6-axis educational robot created for practical and affordable teaching of robotics in schools and beyond. It has been created with 3D printing, so it allows for experimentation and the possible addition of parts. With its design and programming, it replicates the actions of #KawasakiRobotics industrial robots, giving students the necessary skills for future work.

[ Astorino ]

I guess fish-fillet-shaping robots need to exist because otherwise customers will freak out if all their fish fillets are not identical, or something?

[ Flexiv ]

Watch the second episode of the ExoMars Rosalind Franklin rover mission—Europe’s ambitious exploration journey to search for past and present signs of life on Mars. The rover will dig, collect, and investigate the chemical composition of material collected by a drill. Rosalind Franklin will be the first rover to reach a depth of up to two meters below the surface, acquiring samples that have been protected from surface radiation and extreme temperatures.

[ ESA ]

The software used to control a robot is normally highly adapted to its specific physical set up. But now researchers have created a single general-purpose robotic control policy that can operate robotic arms, wheeled robots, quadrupeds, and even drones.

One of the biggest challenges when it comes to applying machine learning to robotics is the paucity of data. While computer vision and natural language processing can piggyback off the vast quantities of image and text data found on the Internet, collecting robot data is costly and time-consuming.

To get around this, there have been growing efforts to pool data collected by different groups on different kinds of robots, including the Open X-Embodiment and DROID datasets. The hope is that training on diverse robotics data will lead to “positive transfer,” which refers to when skills learned from training on one task help to boost performance on another.

The problem is that robots often have very different embodiments—a term used to describe their physical layout and suite of sensors and actuators—so the data they collect can vary significantly. For instance, a robotic arm might be static, have a complex arrangement of joints and fingers, and collect video from a camera on its wrist. In contrast, a quadruped robot is regularly on the move and relies on force feedback from its legs to maneuver. The kinds of tasks and actions these machines are trained to carry out are also diverse: The arm may pick and place objects, while the quadruped needs keen navigation.

That makes training a single AI model for robots on these large collections of data challenging, says Homer Walke, a Ph.D. student at the University of California, Berkeley. So far, most attempts have either focused on data from a narrower selection of similar robots or researchers have manually tweaked data to make observations from different robots more similar. But in research to be presented at the Conference on Robot Learning (CoRL) in Munich in November, they unveiled a new model called CrossFormer that can train on data from a diverse set of robots and control them just as well as specialized control policies.

“We want to be able to train on all of this data to get the most capable robot,” says Walke. “The main advance in this paper is working out what kind of architecture works the best for accommodating all these varying inputs and outputs.”

How to control diverse robots with the same AI model

The team used the same model architecture that powers large language model, known as a transformer. In many ways, the challenge the researchers were trying to solve is not dissimilar to that facing a chatbot, says Walke. In language modeling, the AI has to to pick out similar patterns in sentences with different lengths and word orders. Robot data can also be arranged in a sequence much like a written sentence, but depending on the particular embodiment, observations and actions vary in length and order too.

“Words might appear in different locations in a sentence, but they still mean the same thing,” says Walke. “In our task, an observation image might appear in different locations in the sequence, but it’s still fundamentally an image and we still want to treat it like an image.”

UC Berkeley/Carnegie Mellon University

Most machine learning approaches work through a sequence one element at a time, but transformers can process the entire stream of data at once. This allows them to analyze the relationship between different elements and makes them better at handling sequences that are not standardized, much like the diverse data found in large robotics datasets.

Walke and his colleagues aren’t the first to train transformers on large-scale robotics data. But previous approaches have either trained solely on data from robotic arms with broadly similar embodiments or manually converted input data to a common format to make it easier to process. In contrast, CrossFormer can process images from cameras positioned above a robot, at head height or on a robotic arms wrist, as well as joint position data from both quadrupeds and robotic arms, without any tweaks.

The result is a single control policy that can operate single robotic arms, pairs of robotic arms, quadrupeds, and wheeled robots on tasks as varied as picking and placing objects, cutting sushi, and obstacle avoidance. Crucially, it matched the performance of specialized models tailored for each robot and outperformed previous approaches trained on diverse robotic data. The team even tested whether the model could control an embodiment not included in the dataset—a small quadcopter. While they simplified things by making the drone fly at a fixed altitude, CrossFormer still outperformed the previous best method.

“That was definitely pretty cool,” says Ria Doshi, an undergraduate student at Berkeley. “I think that as we scale up our policy to be able to train on even larger sets of diverse data, it’ll become easier to see this kind of zero shot transfer onto robots that have been completely unseen in the training.”

The limitations of one AI model for all robots

The team admits there’s still work to do, however. The model is too big for any of the robots’ embedded chips and instead has to be run from a server. Even then, processing times are only just fast enough to support real-time operation, and Walke admits that could break down if they scale up the model. “When you pack so much data into a model it has to be very big and that means running it for real-time control becomes difficult.”

One potential workaround would be to use an approach called distillation, says Oier Mees, a postdoctoral research at Berkley and part of the CrossFormer team. This essentially involves training a smaller model to mimic the larger model, and if successful can result in similar performance for a much smaller computational budget.

But of more importance than the computing resource problem is that the team failed to see any positive transfer in their experiments, as CrossFormer simply matched previous performance rather than exceeding it. Walke thinks progress in computer vision and natural language processing suggests that training on more data could be the key.

Others say it might not be that simple. Jeannette Bohg, a professor of robotics at Stanford University, says the ability to train on such a diverse dataset is a significant contribution. But she wonders whether part of the reason why the researchers didn’t see positive transfer is their insistence on not aligning the input data. Previous research that trained on robots with similar observation and action data has shown evidence of such cross-overs. “By getting rid of this alignment, they may have also gotten rid of this significant positive transfer that we’ve seen in other work,” Bohg says.

It’s also not clear if the approach will boost performance on tasks specific to particular embodiments or robotic applications, says Ram Ramamoorthy, a robotics professor at Edinburgh University. The work is a promising step towards helping robots capture concepts common to most robots, like “avoid this obstacle,” he says. But it may be less useful for tackling control problems specific to a particular robot, such as how to knead dough or navigate a forest, which are often the hardest to solve.

Where’s your flying car? I’m sorry to say that I have no idea. But here’s something that is somewhat similar, in that it flies, transports things, and has “car” in the name: it’s a flying cart, called the Palletrone (pallet+drone), designed for human-robot interaction-based aerial cargo transportation.

The way this thing works is fairly straightforward. The Palletrone will try to keep its roll and pitch at zero, to make sure that there’s a flat and stable platform for your preciouses, even if you don’t load those preciouses onto the drone evenly. Once loaded up, the drone relies on you to tell it where to go and what to do, using its IMU to respond to the slightest touch and translating those forces into control over the Palletrone’s horizontal, vertical, and yaw trajectories. This is particularly tricky to do, because the system has to be able to differentiate between the force exerted by cargo, and the force exerted by a human, since if the IMU senses a force moving the drone downward, it could be either. But professor Seung Jae Lee tells us that they developed “a simple but effective method to distinguish between them.”

Since the drone has to do all of this sensing and movement without pitching or rolling (since that would dump its cargo directly onto the floor) it’s equipped with internal propeller arms that can be rotated to vector thrust in any direction. We were curious about how having a bunch of unpredictable stuff sitting right above those rotors might affect the performance of the drone. But Seung Jae Lee says that the drone’s porous side structures allow for sufficient airflow and that even when the entire top of the drone is covered, thrust is only decreased by about 5 percent.

The current incarnation of the Palletrone is not particularly smart, and you need to remain in control of it, although if you let it go it will do its best to remain stationary (until it runs out of batteries). The researchers describe the experience of using this thing as “akin to maneuvering a shopping cart,” although I would guess that it’s somewhat noisier. In the video, the Palletrone is loaded down with just under 3 kilograms of cargo, which is respectable enough for testing. The drone is obviously not powerful enough to haul your typical grocery bag up the stairs to your apartment. But, it’s a couple of steps in the right direction, at least.

We also asked Seung Jae Lee about how he envisions the Palletrone being used, besides as just a logistics platform for either commercial or industrial use. “By attaching a camera to the platform, it could serve as a flying tripod or even act as a dolly, allowing for flexible camera movements and angles,” he says. “This would be particularly useful in environments where specialized filming equipment is difficult to procure.”

And for those of you about to comment something along the lines of, “this can’t possibly have enough battery life to be real-world useful,” they’re already working to solve that, with a docking system that allows one Palletrone to change the battery of another in-flight:

One Palletrone swaps out the battery of a second Palletrone.Seoul Tech

“The Palletrone Cart: Human-Robot Interaction-Based Aerial Cargo Transportation,” by Geonwoo Park, Hyungeun Park, Wooyong Park, Dongjae Lee, Murim Kim, and Seung Jae Lee from Seoul National University of Science and Technology in Korea, is published in IEEE Robotics And Automation Letters.

This is a sponsored article brought to you by Khalifa University of Science and Technology.

A total of eight intense competitions to inspire creativity and innovation along with 13 forums dedicated to diverse segments of robotics and artificial intelligence will be part of the 36th edition of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2024) in Abu Dhabi.

These competitions at the Middle East and North Africa (MENA) region’s first-ever global conference and exhibition from 14-18 October 2024 at the Abu Dhabi National Exhibition Center (ADNEC) will highlight some of the key aspects of robotics. These include physical or athletic intelligence of robots, remote robot navigation, robot manipulation, underwater robotics, perception and sensing as well as challenges for wildlife preservation.

This edition of IROS is one of the largest of its kind globally in this category because of active participation across all levels, with 5,740 authors, 16 keynote speakers, 46 workshops, 11 tutorials, as well as 28 exhibitors and 12 startups. The forums at IROS will explore the rapidly evolving role of robotics in many industry sectors as well as policy-making and regulatory areas. Several leading corporate majors, and industry professionals from across the globe are gathering for IROS 2024 which is themed “Robotics for Sustainable Development.”

“The intense robotics competitions will inspire creativity, while the products on display as well as keynotes will pave the way for more community-relevant solutions.” —Jorge Dias, IROS 2024 General Chair

Dr. Jorge Dias, IROS 2024 General Chair, said: “Such a large gathering of scientists, researchers, industry leaders and government stakeholders in Abu Dhabi for IROS 2024 also demonstrates the role of UAE in pioneering new technologies and in providing an international platform for knowledge exchange and sharing of expertise. The intense robotics competitions will inspire creativity, while the products on display as well as keynotes will pave the way for more community-relevant solutions.”

The competitions are:

• 2nd AI Olympics With RealAIGym: Is AI Ready for Athletic Intelligence in the Real World? focusing on the physical or athletic intelligence of robots

• The Earth Rovers Challenge on remote robot navigation

• Robotic Construction Challenge and the euROBIN Manipulation Skill Versatility Challenge (MSVC) on robot manipulation

• Underwater Robotics Challenges on innovation and problem-solving in underwater robotics and artificial intelligence

• ROAD-IROS: Automatic Data Annotation Challenge for ROAD Dataset on perception and sensing

• 21st F1Tenth Autonomous Racing Competition

• IEEE RAS Quadruped Robot Challenge (QRC), focusing on navigation

In addition to these competitions, the Falcon Monitoring Challenge (FMC) will focus on advancing the field of wildlife tracking and conservation through the development of sophisticated, noninvasive monitoring systems.

Khalifa University

IROS 2024 will also include three keynote talks on ‘Robotic Competitions’ that will be moderated by Professor Lakmal Seneviratne, Director, Center for Autonomous Robotic Systems (KU-CARS), Khalifa University. The keynotes will be delivered by Professor Pedro Lima, Institute for Systems and Robotics, Instituto Superior Técnico, University of. Lisbon, Portugal; Dr. Timothy Chung, General Manager, Autonomy and Robotics, Microsoft, US; and Dr. Ubbo Visser, President of the RoboCup Federation, Director of Graduate Studies, and Associate Professor of Computer Science, University of Miami, US.

The forums at IROS 2024 will include:

• Robotics in Africa Forum

• Marine Robotics in Ocean Decade Initiative for Sustainable Development

• Robots for Sustainability and Sustainable Robots

• Government Forum: Funding for Robotics Research, Human-Avatars Symbiosis: Can you imagine a future society where you can remotely control multiple avatars?

• Moonshot R&D Program Goal 3 Forum. Envisioning a Future of Human-Robot Co-living: Potential for Robotics to Transform Human Lives

Other forums include:

• Sustainable Medical and Surgical Robotics

• Empowering Diverse Voices in Robotics, Robotics & AI in the UAE: Research Innovation and Entrepreneurship

• Europe Regulates Artificial Intelligence: the Challenge for Robotics, Industrial Opportunities and Socio-Economic Impact of Medical Robotics

• The Future of Work: AI-Enhanced Robotics and Human Interaction Research in M3S

• Robots for a Better Tomorrow: Wellbeing Through Advanced Technology.

One of the largest and most important robotics research conferences in the world, IROS 2024 provides a platform for the international robotics community to exchange knowledge and ideas about the latest advances in intelligent robots and smart machines. A total of 3,344 paper submissions representing 60 countries, have been received from researchers and scientists across the world. China tops the list with more than 1,000 papers, the US with 777, Germany with 302, Japan with 253, and the UK and South Korea with 173 each. The UAE remains top in the Arab region with 68 papers.

One of the largest and most important robotics research conferences in the world, IROS 2024 provides a platform for the international robotics community to exchange knowledge and ideas.

For eight consecutive years since 2017, Abu Dhabi has remained first on the world’s safest cities list, according to online database Numbeo, which assessed 329 global cities for the 2024 listing. This reflects the emirate’s ongoing efforts to ensure a good quality of life for citizens and residents. With a multicultural community, Abu Dhabi is home to people from more than 200 nationalities, and draws a large number of tourists to some of the top art galleries in the city such as Louvre Abu Dhabi and the Guggenheim Abu Dhabi, as well as other destinations such as Ferrari World Abu Dhabi and Warner Bros. World™ Abu Dhabi.

Because of its listing as one of the safest cities, Abu Dhabi continues to host several international conferences and exhibitions. Abu Dhabi is set to host the UNCTAD World Investment Forum, the 13th World Trade Organization (WTO) Ministerial Conference (MC13), the 12th World Environment Education Congress in 2024, and the IUCN World Conservation Congress in 2025.

IROS 2024 is sponsored by IEEE Robotics and Automation Society, Abu Dhabi Convention and Exhibition Bureau, the Robotics Society of Japan (RSJ), the Society of Instrument and Control Engineers (SICE), the New Technology Foundation, and the IEEE Industrial Electronics Society (IES).

More information at https://iros2024-abudhabi.org/