It is thought that humans can only maintain relationships with around 150 people, a figure known as Dunbar's number, but it seems that AI models can outstrip this and reach consensus in far bigger groups

A simulator for the process of scientific discovery shows that AI models still fall short of human scientists and engineers in coming up with hypotheses and carrying out experiments on their own

Next-generation phone networks could dramatically outperform current ones thanks to a new technique for transmitting multiple streams of data over a wide range of frequencies

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

Is Jessie available to babysit again?

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!

The National Science Foundation Human AugmentatioN via Dexterity Engineering Research Center (HAND ERC) was announced in August 2024. Funded for up to 10 years and $52 million, the HAND ERC is led by Northwestern University, with core members Texas A&M, Florida A&M, Carnegie Mellon, and MIT, and support from Wisconsin-Madison, Syracuse, and an innovation ecosystem consisting of companies, national labs, and civic and advocacy organizations. HAND will develop versatile, easy-to-use dexterous robot end effectors (hands).

[ HAND ]

The Environmental Robotics Lab at ETH Zurich, in partnership with Wilderness International (and some help from DJI and Audi), is using drones to sample DNA from the tops of trees in the Peruvian rainforest. Somehow, the treetops are where 60 to 90 percent of biodiversity is found, and these drones can help researchers determine what the heck is going on up there.

[ ERL ]

Thanks, Steffen!

1X introduces NEO Beta, “the pre-production build of our home humanoid.”

“Our priority is safety,” said Bernt Børnich, CEO at 1X. “Safety is the cornerstone that allows us to confidently introduce NEO Beta into homes, where it will gather essential feedback and demonstrate its capabilities in real-world settings. This year, we are deploying a limited number of NEO units in selected homes for research and development purposes. Doing so means we are taking another step toward achieving our mission.”

[ 1X ]

We love MangDang’s fun and affordable approach to robotics with Mini Pupper. The next generation of the little legged robot has just launched on Kickstarter, featuring new and updated robots that make it easy to explore embodied AI.

The Kickstarter is already fully funded after just a day or two, but there are still plenty of robots up for grabs.

[ Kickstarter ]

Quadrupeds in space can use their legs to reorient themselves. Or, if you throw one off a roof, it can learn to land on its feet.

To be presented at CoRL 2024.

[ ARL ]

HEBI Robotics, which apparently was once headquartered inside a Pittsburgh public bus, has imbued a table with actuators and a mind of its own.

[ HEBI Robotics ]

Carcinization is a concept in evolutionary biology where a crustacean that isn’t a crab eventually becomes a crab. So why not do the same thing with robots? Crab robots solve all problems!

[ KAIST ]

Waymo is smart, but also humans are really, really dumb sometimes.

[ Waymo ]

The Robotics Department of the University of Michigan created an interactive community art project. The group that led the creation believed that while roboticists typically take on critical and impactful problems in transportation, medicine, mobility, logistics, and manufacturing, there are many opportunities to find play and amusement. The final piece is a grid of art boxes, produced by different members of our robotics community, which offer an eight-inch-square view into their own work with robotics.

[ Michigan Robotics ]

I appreciate that UBTECH’s humanoid is doing an actual job, but why would you use a humanoid for this?

[ UBTECH ]

I’m sure most actuators go through some form of life-cycle testing. But if you really want to test an electric motor, put it into a BattleBot and see what happens.

[ Hardcore Robotics ]

Yes, but have you tried fighting a BattleBot?

[ AgileX ]

In this video, we present collaboration aerial grasping and transportation using multiple quadrotors with cable-suspended payloads. Grasping using a suspended gripper requires accurate tracking of the electromagnet to ensure a successful grasp while switching between different slack and taut modes. In this work, we grasp the payload using a hybrid control approach that switches between a quadrotor position control and a payload position control based on cable slackness. Finally, we use two quadrotors with suspended electromagnet systems to collaboratively grasp and pick up a larger payload for transportation.

[ Hybrid Robotics ]

I had not realized that the floretizing of broccoli was so violent.

[ Oxipital ]

While the RoboCup was held over a month ago, we still wanted to make a small summary of our results, the most memorable moments, and of course an homage to everyone who is involved with the B-Human team: the team members, the sponsors, and the fans at home. Thank you so much for making B-Human the team it is!

[ B-Human ]

When we think of grasping robots, we think of manipulators of some sort on the ends of arms of some sort. Because of course we do—that’s how (most of us) are built, and that’s the mindset with which we have consequently optimized the world around us. But one of the great things about robots is that they don’t have to be constrained by our constraints, and at ICRA@40 in Rotterdam this week, we saw a novel new Thing: a robotic hand that can detach from its arm and then crawl around to grasp objects that would be otherwise out of reach, designed by roboticists from EPFL in Switzerland.

Fundamentally, robot hands and crawling robots share a lot of similarities, including a body along with some wiggly bits that stick out and do stuff. But most robotic hands are designed to grasp rather than crawl, and as far as I’m aware, no robotic hands have been designed to do both of those things at the same time. Since both capabilities are important, you don’t necessarily want to stick with a traditional grasping-focused hand design. The researchers employed a genetic algorithm and simulation to test a bunch of different configurations in order to optimize for the ability to hold things and to move.

You’ll notice that the fingers bend backwards as well as forwards, which effectively doubles the ways in which the hand (or, “Handcrawler”) can grasp objects. And it’s a little bit hard to tell from the video, but the Handcrawler attaches to the wrist using magnets for alignment along with a screw that extends to lock the hand into place.

“Although you see it in scary movies, I think we’re the first to introduce this idea to robotics.” —Xiao Gao, EPFL

The whole system is controlled manually in the video, but lead author Xiao Gao tells us that they already have an autonomous version (with external localization) working in the lab. In fact, they’ve managed to run an entire grasping sequence autonomously, with the Handcrawler detaching from the arm, crawling to a location the arm can’t reach, picking up an object, and then returning and reattaching itself to the arm again.

Scientists say geoengineering, or doing things like intentionally increasing Earth’s reflectivity or blocking the sun, is a “really big deal” in slowing down climate change. Here are the ideas they are proposing.

ROGER FEDERER has explained why he gets injured less than rivals Rafael Nadal and Novak Djokovic..

Liverpool already have one song synonymous with the club but they did attempt to officially do likewise with another. The Reds tried to trademark 'Allez Allez Allez'..

SpaceX pulled off a stunning achievement this week, conducting four launches in less than 48 hours with huge implications for the future of space exploration.

As many as 115 Post Office Branches and hundreds of jobs could be at risk following a strategic review held by Post Office Chairman Nigel Railton.

Genetic testing on samples collected during the earliest days of the covid-19 outbreak suggests it is likely that the virus spread from animals to humans at the Huanan seafood market

Our immune cells change a lot as the decades progress, which could explain why we become more susceptible to certain conditions

Antibiotics can reduce diversity in the gut microbiome, raising the risk of infections that cause diarrhoea - and the effects may last years

Our metabolism's response to food is highly idiosyncratic and there are hints that tailoring our diet to these personal differences can deliver health benefits

Chronic pain has increased among adults in the US since 2019, which could be due to a rise in sedentary lifestyles or reduced access to healthcare amid covid-19 restrictions

On Tuesday, three of nine ballot issues Denver voters had to decide dealt with animals and animal products. But nothing changed because all of them were slaughtered at the ballot  box. One of the ballot issues called for prohibiting any slaughterhouse from operating in the City or County of Denver. That... Continue Reading

Israel has proposed a revised system of food business licensing to ease the regulatory burden on industry and improve sanitary conditions. The Ministry of Health said the current regulation, regarding business licensing in general and food businesses in particular, is outdated and places a heavy regulatory burden on companies. This... Continue Reading

Fox News host Sean Hannity says the "decentralization of power as our founders intended is very much on its way to DC."

The end of Moore’s Law is looming. Engineers and designers can do only so much to miniaturize transistors and pack as many of them as possible into chips. So they’re turning to other approaches to chip design, incorporating technologies like AI into the process.

Samsung, for instance, is adding AI to its memory chips to enable processing in memory, thereby saving energy and speeding up machine learning. Speaking of speed, Google’s TPU V4 AI chip has doubled its processing power compared with that of its previous version.

But AI holds still more promise and potential for the semiconductor industry. To better understand how AI is set to revolutionize chip design, we spoke with Heather Gorr, senior product manager for MathWorks’ MATLAB platform.

How is AI currently being used to design the next generation of chips?

Heather Gorr: AI is such an important technology because it’s involved in most parts of the cycle, including the design and manufacturing process. There’s a lot of important applications here, even in the general process engineering where we want to optimize things. I think defect detection is a big one at all phases of the process, especially in manufacturing. But even thinking ahead in the design process, [AI now plays a significant role] when you’re designing the light and the sensors and all the different components. There’s a lot of anomaly detection and fault mitigation that you really want to consider.

Heather GorrMathWorks

Then, thinking about the logistical modeling that you see in any industry, there is always planned downtime that you want to mitigate; but you also end up having unplanned downtime. So, looking back at that historical data of when you’ve had those moments where maybe it took a bit longer than expected to manufacture something, you can take a look at all of that data and use AI to try to identify the proximate cause or to see something that might jump out even in the processing and design phases. We think of AI oftentimes as a predictive tool, or as a robot doing something, but a lot of times you get a lot of insight from the data through AI.

What are the benefits of using AI for chip design?

Gorr: Historically, we’ve seen a lot of physics-based modeling, which is a very intensive process. We want to do a reduced order model, where instead of solving such a computationally expensive and extensive model, we can do something a little cheaper. You could create a surrogate model, so to speak, of that physics-based model, use the data, and then do your parameter sweeps, your optimizations, your Monte Carlo simulations using the surrogate model. That takes a lot less time computationally than solving the physics-based equations directly. So, we’re seeing that benefit in many ways, including the efficiency and economy that are the results of iterating quickly on the experiments and the simulations that will really help in the design.

So it’s like having a digital twin in a sense?

Gorr: Exactly. That’s pretty much what people are doing, where you have the physical system model and the experimental data. Then, in conjunction, you have this other model that you could tweak and tune and try different parameters and experiments that let sweep through all of those different situations and come up with a better design in the end.

So, it’s going to be more efficient and, as you said, cheaper?

Gorr: Yeah, definitely. Especially in the experimentation and design phases, where you’re trying different things. That’s obviously going to yield dramatic cost savings if you’re actually manufacturing and producing [the chips]. You want to simulate, test, experiment as much as possible without making something using the actual process engineering.

We’ve talked about the benefits. How about the drawbacks?

Gorr: The [AI-based experimental models] tend to not be as accurate as physics-based models. Of course, that’s why you do many simulations and parameter sweeps. But that’s also the benefit of having that digital twin, where you can keep that in mind—it’s not going to be as accurate as that precise model that we’ve developed over the years.

Both chip design and manufacturing are system intensive; you have to consider every little part. And that can be really challenging. It’s a case where you might have models to predict something and different parts of it, but you still need to bring it all together.

One of the other things to think about too is that you need the data to build the models. You have to incorporate data from all sorts of different sensors and different sorts of teams, and so that heightens the challenge.

How can engineers use AI to better prepare and extract insights from hardware or sensor data?

Gorr: We always think about using AI to predict something or do some robot task, but you can use AI to come up with patterns and pick out things you might not have noticed before on your own. People will use AI when they have high-frequency data coming from many different sensors, and a lot of times it’s useful to explore the frequency domain and things like data synchronization or resampling. Those can be really challenging if you’re not sure where to start.

One of the things I would say is, use the tools that are available. There’s a vast community of people working on these things, and you can find lots of examples [of applications and techniques] on GitHub or MATLAB Central, where people have shared nice examples, even little apps they’ve created. I think many of us are buried in data and just not sure what to do with it, so definitely take advantage of what’s already out there in the community. You can explore and see what makes sense to you, and bring in that balance of domain knowledge and the insight you get from the tools and AI.

What should engineers and designers consider when using AI for chip design?

Gorr: Think through what problems you’re trying to solve or what insights you might hope to find, and try to be clear about that. Consider all of the different components, and document and test each of those different parts. Consider all of the people involved, and explain and hand off in a way that is sensible for the whole team.

How do you think AI will affect chip designers’ jobs?

Gorr: It’s going to free up a lot of human capital for more advanced tasks. We can use AI to reduce waste, to optimize the materials, to optimize the design, but then you still have that human involved whenever it comes to decision-making. I think it’s a great example of people and technology working hand in hand. It’s also an industry where all people involved—even on the manufacturing floor—need to have some level of understanding of what’s happening, so this is a great industry for advancing AI because of how we test things and how we think about them before we put them on the chip.

How do you envision the future of AI and chip design?

Gorr: It’s very much dependent on that human element—involving people in the process and having that interpretable model. We can do many things with the mathematical minutiae of modeling, but it comes down to how people are using it, how everybody in the process is understanding and applying it. Communication and involvement of people of all skill levels in the process are going to be really important. We’re going to see less of those superprecise predictions and more transparency of information, sharing, and that digital twin—not only using AI but also using our human knowledge and all of the work that many people have done over the years.

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

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

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

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

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

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

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

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

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

How many takes did this take?

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

Is this a task that humans currently do?

Kuindersma: Yes.

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

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

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

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

Are the head and torso capable of unlimited rotation?

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

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

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

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

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

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

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

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

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

How many important sensors does the hot dog costume occlude?

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

Why are pickles always causing problems?

Kuindersma: Because pickles are pesky, polarizing pests.

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

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

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

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

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

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

Oceans Absorb Less CO₂ Than Expected

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

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

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

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

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

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

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

Slower Marine Snow Reduces Carbon Sequestration

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

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

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

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

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

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

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

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

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

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

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

Enjoy today’s videos!

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

[ Unitree Robotics ]

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

[ Meta ]

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

[ Clone Inc. ]

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

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

Thanks, Duncan!

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

[ CubiXMusashi, JSK Robotics Laboratory, University of Tokyo ]

Thanks, Shintaro!

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

[ Agility Robotics ]

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

[ Disney Research paper ]

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

[ Engineai ]

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

[ Paper University of Pennsylvania and University of Zurich ]

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

[ LEGATO ]

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

[ Robot Era ]

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

[ CyberKnights ]

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

[ PAL Robotics ]

Thanks, Rugilė!

Samples from the asteroid Ryugu contain key ingredients in the biological cookbook.

It's not the reach of a fire that matters most; it's the speed. Understanding this can help society better prepare.

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Researchers show the average surface temperature on our planet has shifted between 51.8 to 96.8 degrees Fahrenheit

Fluff and fuzz helped the creatures keep warm, blend in and communicate

An ecologist’s long walks and detailed observations allowed him to chronicle the shifts in an iconic habitat and grow a once-overlooked branch of science

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We spoke to Dr Ian Paul, who is a reverend and member of General Synod and the Archbishops’ Council.

The business secretary Jonathan Reynolds has called for a change of culture at the Post Office, as he gave evidence to the inquiry into the Horizon scandal.

We spoke to one of John Smyth’s victims, Mark Stibbe, a former vicar and now an author.

Starship will launch during the late afternoon so its descent into Indian Ocean is visible.

A younger rival may have learned how to sabotage those showers by disrupting water flow.

"The goal is to complete the password updates by this evening," government says.

Time-hopping film Here used AI trained on every Tom Hanks movie to make him appear young again.

The office of the U.S. Special Inspector General for Afghanistan Reconstruction (SIGAR), a federal watchdog agency, revealed in its regular report that China has held more than 200 meetings with Taliban terrorists since their return to power, Afghanistan's Tolo News reported this weekend.

The post U.S. Watchdog Report: China Holds More Meetings with Taliban than Any Other Country appeared first on Breitbart.

In a 5-4 decision, the Supreme Court struck down a key provision of the Voting Rights Act of 1965, stating that the legislation was based on now outdated data. The ruling removes the coverage formula that required federal oversight for voting processes in nine states.

On May 13, 1985, after a long standoff, Philadelphia municipal authorities dropped a bomb on the headquarters of the African-American radical group MOVE. In the documentary Let the Fire Burn, director Jason Osder uses archival footage to chronicle the years of tension that ended in tragedy.

In a 5-4 decision in U.S. v. Windsor, the Supreme Court ruled the federal Defense Of Marriage Act unconstitutional. The court rules that supporters of California's Proposition 8 case did not have standing to bring the case to court, which means same-sex marriages in California may resume.