Humanoids

ADAPT robotic hand (Adaptive Dexterous Anthropomorphic Programmable sTiffness) © CREATE Lab EPFL

A robotic hand developed at EPFL can pick up 24 different objects with human-like movements that emerge spontaneously, thanks to compliant materials and structures rather than programming.

Robotic hand moves objects with human-like grasps

MIT engineers are getting in on the robotic ping pong game with a powerful, lightweight design that returns shots with high-speed precision.The new table tennis bot comprises a multijointed robotic arm that is fixed to one end of a ping pong table and wields a standard ping pong paddle. Aided by several high-speed cameras and a high-bandwidth predictive control system, the robot quickly estimates the speed and trajectory of an incoming ball and executes one of several swing types — loop, drive, or chop — to precisely hit the ball to a desired location on the table with various types of spin.In tests, the engineers threw 150 balls at the robot, one after the other, from across the ping pong table. The bot successfully returned the balls with a hit rate of about 88 percent across all three swing types. The robot’s strike speed approaches the top return speeds of human players and is faster than that of other robotic table tennis designs.<iframe width="640" height="360" src="https://www.youtube.com/embed/FqyKfi_myLM?&amp;wmode=opaque&amp;enablejsapi=1&amp;origin=https://www.wevolver.com" frameborder="0" class="fr-draggable"></iframe>Now, the team is looking to increase the robot’s playing radius so that it can return a wider variety of shots. Then, they envision the setup could be a viable competitor in the growing field of smart robotic training systems.Beyond the game, the team says the table tennis tech could be adapted to improve the speed and responsiveness of humanoid robots, particularly for search-and-rescue scenarios, and situations in a which a robot would need to quickly react or anticipate.“The problems that we’re solving, specifically related to intercepting objects really quickly and precisely, could potentially be useful in scenarios where a robot has to carry out dynamic maneuvers and plan where its end effector will meet an object, in real-time,” says MIT graduate student David Nguyen.Nguyen is a co-author of the new study, along with MIT graduate student Kendrick Cancio and Sangbae Kim, associate professor of mechanical engineering and head of the <a href="https://biomimetics.mit.edu/" target="_blank">MIT Biomimetics Robotics Lab</a>. The researchers will present the results of those experiments in a <a href="https://www.arxiv.org/pdf/2505.01617" target="_blank">paper</a> at the IEEE International Conference on Robotics and Automation (ICRA) this month.<h2>Precise play</h2>Building robots to play ping pong is a challenge that researchers have taken up since the 1980s. The problem requires a unique combination of technologies, including high-speed machine vision, fast and nimble motors and actuators, precise manipulator control, and accurate, real-time prediction, as well as higher-level planning of game strategy.“If you think of the spectrum of control problems in robotics, we have on one end manipulation, which is usually slow and very precise, such as picking up an object and making sure you’re grasping it well. On the other end, you have locomotion, which is about being dynamic and adapting to perturbations in your system,” Nguyen explains. “Ping pong sits in between those. You’re still doing manipulation, in that you have to be precise in hitting the ball, but you have to hit it within 300 milliseconds. So, it balances similar problems of dynamic locomotion and precise manipulation.”Ping pong robots have come a long way since the 1980s, most recently with designs by Omron and Google DeepMind that employ artificial intelligence techniques to “learn” from previous ping pong data, to improve a robot’s performance against an increasing variety of strokes and shots. These designs have been shown to be fast and precise enough to rally with intermediate human players.“These are really specialized robots designed to play ping pong,” Cancio says. “With our robot, we are exploring how the techniques used in playing ping pong could translate to a more generalized system, like a humanoid or anthropomorphic robot that can do many different, useful things.”<h2>Game control</h2>For their new design, the researchers modified a lightweight, high-power robotic arm that Kim’s lab developed as part of the MIT Humanoid — a bipedal, two-armed robot that is about the size of a small child. The group is using the robot to test various dynamic maneuvers, including navigating uneven and varying terrain as well as jumping, running, and doing backflips, with the aim of one day deploying such robots for search-and-rescue operations.Each of the humanoid’s arms has four joints, or degrees of freedom, which are each controlled by an electrical motor. Cancio, Nguyen, and Kim built a similar robotic arm, which they adapted for ping pong by adding an additional degree of freedom in the wrist to allow for control of a paddle.The team fixed the robotic arm to a table at one end of a standard ping pong table and set up high-speed motion capture cameras around the table to track balls that are bounced at the robot. They also developed optimal control algorithms that predict, based on the principles of math and physics, what speed and paddle orientation the arm should execute to hit an incoming ball with a particular type of swing: loop (or topspin), drive (straight-on), or chop (backspin).<img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1747231279859-MIT-PingPongRobot-03-press.jpg" style="width:100%px" class="fr-fic fr-dib" />The team fixed the robotic arm to a table at one end of a standard ping pong table and set up high-speed motion capture cameras around the table to track balls that are bounced at the robot. Here, it performs a back spin. Credit: Courtesy of the researchersThey implemented the algorithms using three computers that simultaneously processed camera images, estimated a ball’s real-time state, and translated these estimations to commands for the robot’s motors to quickly react and take a swing.After consecutively bouncing 150 balls at the arm, they found the robot’s hit rate, or accuracy of returning the ball, was about the same for all three types of swings: 88.4 percent for loop strikes, 89.2 percent for chops, and 87.5 percent for drives. They have since tuned the robot’s reaction time and found the arm hits balls faster than existing systems, at velocities of 20 meters per second.In their paper, the team reports that the robot’s strike speed, or the speed at which the paddle hits the ball, is on average 11 meters per second. Advanced human players have been known to return balls at speeds of between 21 to 25 meters second. Since writing up the results of their initial experiments, the researchers have further tweaked the system, and have recorded strike speeds of up to 19 meters per second (about 42 miles per hour).“Some of the goal of this project is to say we can reach the same level of athleticism that people have,” Nguyen says. “And in terms of strike speed, we’re getting really, really close.”Their follow-up work has also enabled the robot to aim. The team incorporated control algorithms into the system that predict not only how but where to hit an incoming ball. With its latest iteration, the researchers can set a target location on the table, and the robot will hit a ball to that same location.Because it is fixed to the table, the robot has limited mobility and reach, and can mostly return balls that arrive within a crescent-shaped area around the midline of the table. In the future, the engineers plan to rig the bot on a gantry or wheeled platform, enabling it to cover more of the table and return a wider variety of shots.“A big thing about table tennis is predicting the spin and trajectory of the ball, given how your opponent hit it, which is information that an automatic ball launcher won’t give you,” Cancio says. “A robot like this could mimic the maneuvers that an opponent would do in a game environment, in a way that helps humans play and improve.”This research is supported, in part, by the Robotics and AI Institute.

Time lapse photos show a new ping-pong-playing robot performing a top spin. The robot quickly estimates the speed and trajectory of an incoming ball and precisely hits it to a desired location on the table. Credit: Courtesy of the researchers

In addition to training future players, the technology could expand the capabilities of other humanoid robots, such as for search and rescue.

Ping pong bot returns shots with high-speed precision

The hospitality industry can leverage the gender characteristics of service robots to influence customers’ decisions, according to new research from a team in the <a href="https://hhd.psu.edu/shm" rel="noreferrer noopener" target="_blank">Penn State School of Hospitality Management</a>.Service robots with characteristics typically associated with males may be more persuasive when interacting with women who have a low sense of power, according to the researchers. The team also found that “cute” features in the design of robots — such as big eyes and raised cheeks — may reduce the effect of portrayed robot gender on persuasiveness, as male and female customers responded similarly to robots with these “cute” features.<a href="https://hhd.psu.edu/contact/lavi-peng" rel="noreferrer noopener" target="_blank">Lavi Peng</a>, doctoral candidate; <a href="https://hhd.psu.edu/contact/anna-mattila" rel="noreferrer noopener" target="_blank">Anna Mattila</a>, Marriott Professor of Lodging Management; and <a href="https://hhd.psu.edu/contact/amit-sharma" rel="noreferrer noopener" target="_blank">Amit Sharma</a>, Edward Friedman and Stuart Mann Professor of Hospitality Management — all at Penn State — led this research. Their findings were published in the <a href="https://doi.org/10.1016/j.jhtm.2025.01.019" rel="noreferrer noopener" target="_blank">Journal of Hospitality and Tourism Management</a>.“Robots can be designed or programed to have human-like features like names, voices and body shapes, which portray gender,” Mattila said. “In addition to robot gender, a consumer’s sense of power — how individuals perceive their ability to influence others or their environment — can also affect how successful a service robot can be in making recommendations.”The researchers conducted two studies to find how the gender portrayed in service robots could influence customers’ decisions.The first study surveyed 239 people who were recruited via Amazon Mechanical Turk. Participants were asked to first rate their sense of power before imagining visiting a new restaurant and receiving a menu recommendation for a breakfast burrito from a service robot. Service robots depicted in the study were the same except for the use of gray or pink colors to portray male or female genders, respectively. After receiving a menu recommendation, participants then rated the robot’s persuasiveness.“We found women with a low sense of power were more prone to accept a male robot’s recommendations,” Peng said. “For men with a low sense of power, we found the difference was less obvious. Based on our findings, consumers with high power tend to make their own judgement without relying on societal expectations. They are more confident and want to make decisions based off their own judgement.”The researchers said restaurants could leverage these findings when deciding what types of service robots to use, such as using “male” robots to recommend new menu items, as the results suggested robots with characteristics typically associated with males can have a greater influence on customer decisions.Hotels could also leverage these findings when deciding which gender characteristics to use in robots that persuade customers to upgrade their rooms, according to the researchers.“Upselling and upgrading are all about persuasion, and results of our study suggested robots with male characteristics could be effective,” Peng said. “If a business knows its customer is female, it may want to consider using a robot with different gender characteristics than it would with a male customer.”The second study investigated how businesses could mitigate gender stereotypes in robot design — or lessen the effect of a “male” robot’s influence on customers with a low sense of power.Because the findings in the first study showed that portrayed gender in robots primarily affected customers with a low sense of power, the researchers recruited 156 university students in the United States. The researchers said <a href="https://doi.org/10.1037/14344-016" rel="noreferrer noopener" target="_blank">prior research</a> demonstrated that students typically hold subordinate positions or rely on faculty members who have authority over their educational outcomes, meaning they represent a low-power demographic.To alter the gender portrayed in robots during the second study, the researchers used an iPad display showing different gendered facial features that topped a Bear Robotics Servi robot, which does not have any typical human-like features of its own. These facial features had “cute” designs, including round faces and big eyes. After being introduced to and interacting with the robot, participants completed a computer-based scenario, evaluating the robot’s recommendation for avocado toast.“Both male and female customers responded similarly to both the male and female robot designs,” Peng said. “For businesses that want to mitigate gender stereotypes, they can consider using a cute design for their robots.”

While service robots with male characteristics can be more persuasive when interacting with some women who have a low sense of power, “cute” design features — such as big eyes and raised cheeks — affect both men and women similarly, according to new research from a team in the Penn State School of Hospitality Management. Credit: Scharfsinn86/Getty Images. All Rights Reserved.

The hospitality industry can leverage the gender characteristics of service robots to influence customers' decisions, according to new research from a team in the Penn State School of Hospitality Management.

Gender characteristics of service robots can influence customer decisions

<h1 id="isPasted">Unitree Introducing | Unitree G1 Humanoid Agent | AI Avatar | Price from $16K</h1>Unlock unlimited sports potential (Extra large joint movement space angle, 23~43 joints) Force control of dexterous hands, manipulation of all thingsImitation &amp; reinforcement learning driven Robot world model, let’s create it together Unitree G1 Price from $16K (Tax and Shipping cost excluded)More introduction: <a href="https://www.youtube.com/redirect?event=video_description&amp;redir_token=QUFFLUhqbk1oNVpGaWU0Ym01Snp2X1RraVpMX2V2VU5wQXxBQ3Jtc0tuQ3MtMHFVakgxZi1iM3prT0IyNURaeVBLblRZa3NreHRCSXBQeXFIWnQ4QnV0TWFzWnFPeXJVWmNCNDctZC1uUkpMalFxWWs0Yzd5a3FhZmpGd2VDanU5YTBEV0RLWUZMV2pta0JrdVVDRjVSdHhHVQ&amp;q=https%3A%2F%2Fwww.unitree.com%2Fg1&amp;v=GzX1qOIO1bE" rel="nofollow" target="_blank">https://www.unitree.com/g1</a>Official Website: www.unitree.com Sales contact: sales_global@unitree.cc

Unlock unlimited sports potential

Unitree Introducing Unitree G1 Humanoid Agent AI Avatar

<h1 id="isPasted">Unitree H1 The World's First Full-size Motor Drive Humanoid Robot Flips on Ground</h1>Unitree H1 Deep Reinforcement Learning In-place Flipping Parameters: Weight: about 50kg Height: about 1.8mActuator: electric motor <a href="https://www.youtube.com/hashtag/unitree" target="_blank">#Unitree</a>  <a href="https://www.youtube.com/hashtag/unitreerobotics" target="_blank">#UnitreeRobotics</a>  <a href="https://www.youtube.com/hashtag/ai" target="_blank">#AI</a> <a href="https://www.youtube.com/hashtag/robotics" target="_blank">#Robotics</a>  <a href="https://www.youtube.com/hashtag/humanoidrobots" target="_blank">#Humanoidrobots</a>   <a href="https://www.youtube.com/hashtag/worldmodel" target="_blank">#Worldmodel</a> <a href="https://www.youtube.com/hashtag/worldrecord" target="_blank">#Worldrecord</a> <a href="https://www.youtube.com/hashtag/flips" target="_blank">#Flips</a> <a href="https://www.youtube.com/hashtag/embodiedai" target="_blank">#EmbodiedAI</a> <a href="https://www.youtube.com/hashtag/artificialintelligence" target="_blank">#ArtificialIntelligence</a> <a href="https://www.youtube.com/hashtag/technology" target="_blank">#Technology</a> <a href="https://www.youtube.com/hashtag/innovation" target="_blank">#Innovation</a> <a href="https://www.youtube.com/hashtag/futureoftech" target="_blank">#futureoftech</a>

Unitree H1 
Deep Reinforcement Learning
In-place Flipping Parameters:
Weight: about 50kg
Height: about 1.8m
Actuator: electric motor

Unitree H1 The World's First Full-size Motor Drive Humanoid Robot Flips on Ground

<h1 id="isPasted">Unitree Iron Fist King: Awakening!</h1>Let's step into a new era of Sci-Fi, join the fun together! Unitree will be livestreaming robot combat in about a month, stay tuned! <h2> </h2>

Let's step into a new era of Sci-Fi, join the fun together!
Unitree will be livestreaming robot combat in about a month, stay tuned!

Unitree Iron Fist King: Awakening!

On the screen, white on a black background, a fly is magnified thousands of times and walks calmly across a spherical surface on its six legs. “Watch, in a second it’ll do the moonwalk.” We are in the heart of the EPFL Neuroengineering Laboratory with Pavan Ramdya, head of the lab, and a postdoctoral researcher, Maite Azcorra. She shines tiny focused pulses of laser light at the fly using a technique known as optogenetics, which uses light to activate specific neurons. As if on command, the fly moves its legs backwards. And it looks just like a dance.Ramdya’s 14-person research group has been studying the nervous system of these two-millimeter-long insects since 2017. “Maite is currently studying how neurons that descend from the brain control motor functions,” says Ramdya. The group hopes to eventually reverse-engineer the fly’s brain and to model it for robotics. One major step forward was the <a href="https://actu.epfl.ch/news/neuromechfly-a-digital-twin-of-drosophila/">development of a digital twin</a> that the researchers can use to accurately simulate a fly’s behaviors; another was an <a href="https://actu.epfl.ch/news/fruit-fly-brain-shows-how-simple-commands-turn-int/">important breakthrough</a> in understanding how neural networks turn brain signals into coordinated movements. We sit down in the office of the New York-born neuroscientist to talk about his work.<h2>Can you describe the general idea behind your research program?</h2>Humans have been trying for centuries to build machines that can behave like animals or people. In Ancient Greece, for example, automated marionettes were quite common – these were simple objects but they were already a form of biomimetics, in that they imitated how an actual body moves. That’s the same idea we’re pursuing here, except that we use far more advanced methods and systems that can truly bio-mimic animals like the fruit fly.<h2>Why are you studying Drosophila melanogaster specifically?</h2>There are more complicated animals of course, like mammals, but they’re harder to study. And there are simpler ones like C.elegans , a worm with only around 300 neurons [flies have around 100,000 and humans have approximately 86 billions] but we can’t learn as much about behavior from them. Unlike worms, flies have legs, and they do a lot with them – walk around, clean themselves, manipulate obstacles and more. It’s much more interesting for applications in robotics and neuroprosthetics to know how a creature with both wings and legs works. They’re perfect specimens from that perspective: simple enough to study, yet complex enough to offer many insights.<h2>In <a href="https://tedxarendal.com/speaker/pavan-ramdya/" target="_blank" rel="noopener">your recent TEDx talk</a>, you said that in the future robots used to explore and colonize new planets might look a lot like these flies.</h2>Yes, robots for space exploration will need to complete numerous tasks on their own and make decisions autonomously while moving in unknown, hostile environments. Engineers have been working to build such robots for decades, but for now, even the most sophisticated machines have nowhere near the agility of the fruit fly. Flies can do incredible things. Not only can they fly, they’re also extremely stable owing to their six legs. They can move in all three dimensions while performing other tasks with their legs. They’re a major source of inspiration!<iframe width="640" height="360" src="https://www.youtube.com/embed/kFV6NC-jIK0?&amp;wmode=opaque&amp;rel=0&amp;enablejsapi=1&amp;origin=https://www.wevolver.com" frameborder="0" class="fr-draggable"></iframe><h2 id="isPasted">How might the work you’re doing influence the development of robotics and AI?</h2>Many engineers are working on the hardware side of robots – for example, batteries and motors. That’s not our focus. We’re seeking to design their controllers. With the idea of developing a robotic fly, our main point of interest is to understand how it can control its limbs. That’s why we’re studying the fruit fly’s nervous system – to gain insights that will help us develop neural networks that can be used in robotics and AI. I’d also point out that the robots using these controllers don’t have to be the size of a fly. As long as it is scaled appropriately, they can be any size – even as big as a house, although that would be a little scary!<h2>But your research includes other aspects, too.</h2>That’s right. One unique characteristic of flies is that their legs are covered with mechanical sensors. How do flies use all the information they gather to understand their environment and detect objects around them? How do they decide when to lift one or more of their legs over obstacles? Those are the kinds of questions we want to answer. And to do that, we’re trying to develop materials patterned after the fly cuticle with integrated sensors that can be used in robots.<h2>Many robotics and AI experts have said that to create machines genuinely capable of learning, the machines must have bodies that can move around and explore their environment.</h2>Yes, that’s a central theory held by scientists studying neurobiology and behavior. And it should be a central theory in AI too, since animals can behave more flexibly than robots. Engineers working in machine learning often point out that human babies constantly move around and touch things, exploring their surroundings to learn about the world around them. This process is much more effective than if we just presented them with videos of their environment. The sensors I mentioned earlier – those on flies – also serve this purpose.<img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1743768163257-b949b203.jpg" style="width:100%px" class="fr-fic fr-dib" />Ramdya’s 14-person research group has been studying the nervous system of these two-millimeter-long insects since 2017. The group hopes to eventually reverse-engineer the fly’s brain and to model it for robotics. - 2025 EPFL/Alain Herzog - CC-BY-SA 4.0<h2 id="isPasted">What are currently the biggest hurdles to developing systems that can learn by exploring their environment?</h2>One hurdle is to create algorithms that can process sensory data. If they can’t contextualize these data, it would be very difficult for machines to learn to learn the appropriate behaviors. It’s important to stress that the solution does exist – it’s just hidden in animals’ nervous systems. That’s what we’re trying to uncover. Instead of spending decades attempting to design a solution from scratch, why not look at what already exists in flies?<h2>Will that necessarily be an easier and faster approach?</h2>What we’ll probably need is a combination of different approaches. Especially since animals have a lot of constraints and objectives that aren’t relevant for our purposes. For instance, robots don’t need to be able to reproduce or defecate. That’s why we must also include biologists in our work and not just engineers. They are better able to know which parts of an organism we can ignore, such as neurons used to evacuate food, so that engineers don’t focus on them. An interdisciplinary approach is essential for the work that we’re doing.<h2>Is the goal to eventually map the human brain?</h2>I’ll have to give you a selfish answer: for me, personally, that’s not my goal. I have around 40 more years to live if I’m lucky, and I’d really like to see major breakthroughs in my lifetime that could show how biological systems work. That seems possible with the fruit fly, but it would be far more complicated for the human brain. Perhaps it’s just a matter of scale – maybe we simply need to take a fly’s brain and multiply it by a million. That might give us something intelligent and would certainly be very interesting. But I’m not sure that it would capture human intelligence. I don’t think we could use exactly the same approach for the human brain as for the fruit fly, because it would take too long.<h2>How is your approach to neuroscience different from that of other neuroscientists?</h2>In neuroscience, I’d say that over 99% of people are working on topics related to human health and medicine. Most studies that examine how neuroscience can inform the treatment of a disease, for instance, are carried out using mice or rats, because they’re mammals like us. I think what our research group is doing can shift people’s perspectives in two ways. First, we look at neuroscience not just in terms of human health, but rather in how it can be applied in robotics to build machines in new ways. And secondly, we draw attention to the smaller fraction of neuroscientists studying insects. We should keep in mind that many of the insects on our planet are under threat. Look at bees, and the important role they play in pollination. It’s a critical issue. Fruit flies aren’t a threatened species but they can provide insight into ones that are, helping to support conservation efforts. This can encourage people to view the world from a more eco-systemic perspective and appreciate the vital contribution made by biodiversity.<hr />BIOPavan Ramdya was born in New York City in 1979 and grew up on Long Island. He’s been interested in robotics ever since he was a child: “I always wondered whether we’d one day be able to build something that looks and acts like a human. It fascinated me.” he says.Upon applying to university, Ramdya initially planned to go into medicine – “when you’re an American of Indian origin, you’re often expected to become either a doctor or an engineer,” he says with a smile. But while preparing his application to study medicine, he changed his mind and focused on neuroscience. He obtained a bachelor’s degree from Drew University, followed by a PhD from Harvard University in 2009.Ramdya came to Lausanne for his postdoctoral research – which is when he began studying fruit flies and robotics – under Richard Benton at the University of Lausanne and Dario Floreano at EPFL. After spending two years as a researcher at Caltech, Ramdya returned to EPFL in 2017 as a professor of Neuroscience and Bioengineering and as head of the Neuroengineering Laboratory. When Ramdya isn’t in the research lab, he may be playing the Fender Jazz Bass guitar that sits proudly in his office. “When I was younger I jammed a lot. I played rock – Led Zeppelin and other groups like that,” he says. “Now I play whenever I have the time. I like all kinds of music.” Does his groove match his talents as a scientist? You can find out today, on <a href="https://memento.epfl.ch/event/sv-band-live-concert-2025/">4 April</a>, when he’ll be performing at the Polydôme with the SV Band.

Pavan Ramdya - 2025 EPFL/Alain Herzog - CC-BY-SA 4.0

Researchers at EPFL’s Neuroengineering Laboratory, led by Pavan Ramdya, aim to replicate the workings of the brain of the common fruit fly, Drosophila melanogaster. We spoke with Ramdya about the exciting prospects for robotics.

"Fruit flies are a major source of inspiration in robotics"

Ghost Dance is a research project out of Lusófona University that sets out to explore the value of human connection and how it can be recreated with a virtual dance partner. Project directors Cecilia de Lima and Rui Antunes looked to inertial motion capture to create fluid motions that real-life dancers could perform alongside. Challenge: The Ghost Dance team needed to build a 3D model based on dancers' movements to test the relationship between virtual and real-life performers. Creating a realistic model posed a significant challenge. Solution: Inertial motion capture technology allowed dancers to record an entire routine with maximum comfort and accuracy. The result was a virtual partner with smooth motions, making for a natural performance with its real-life counterpart.Key takeaways <ul><li>A diverse range of motion: Even complex movements in contemporary dance can be tracked with inertial sensors</li><li>Efficient recording: Entire choreographed performances were recorded quickly, to work around time restrictions in the dance studio</li><li>Comfortable wear: Dancers could perform unobstructed thanks to the adjustable nature of Xsens wearable technology</li><li>Fluid results: The virtual dance partner moved smoothly, creating a high sense of realism during the performance</li></ul>Studying the importance of human touchBefore beginning the project, the <a href="https://ghostdance.ulusofona.pt/outcomes/publications" target="_blank" rel="noopener noreferrer">Ghost Dance</a> directors had two main goals. “The first was to understand the need for physical, bodily presence between humans,” says Rui Antunes, Director. “In the new era of technology, we seem to be growing further apart, and we wanted to see whether this had an impact on our wellbeing.” To explore this, the team planned to use VR goggles to compare dancing with a human partner and a virtual counterpart. “We wanted to find out what happens when a human body interacts with a virtual entity,” explains Cecilia de Lima, Director. “We knew it would make for a completely different experience, but we needed to find out how and why.” The other part of Cecilia and Rui’s project was to see if virtual dance partners could improve via machine learning. The digital counterparts were created from the dancer’s movements, but they wanted to see if they could develop their own routines based on the information provided.To achieve these goals, extensive planning was put into place to find the right technology.<img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1742888563673-Ghost+dance+Performance+Dancing+a+duet+with+avatar+2.jpg" style="width:100%px" class="fr-fic fr-dib" />Building a virtual dance partner This complex project required not only a skilled team, but a set of specialized technology to record the dancers’ performances and transform them into a digital counterpart.Dancers use movements that aren’t typical in day-to-day life, so it was crucial to have a motion capture system to accommodate that complexity. “The Xsens system could accurately record their movements for a perfect translation into a 3D model,” says Rui. Inertial sensors contain accelerometers and gyroscopes, tracking the joint rotation and velocity of the subject. This pinpoint precision allowed for lifelike movements in the virtual dance partner, making a more natural experience for the real-life dancers.“Comfort is essential when dancing,” explains Cecilia. “We needed the motion capture technology to be unobtrusive to get the best results.” The system consists of 17 sensors, which all strap individually onto the body, making each one adjustable to the wearer’s preferences. Having this comfort led to more natural, fluid moves to create the virtual partner. <img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1742888595821-Ghost+dance+Motion+Capture+for+Avatar+Dance+duets+7.jpg" style="width:100%px" class="fr-fic fr-dib" />Machine learning for virtual dance partnersAfter the dancers were recorded and the virtual partners were made, Cecilia and Rui needed to see whether they could develop from the base-level data. To do this, they created machine-learning algorithms to put the models to the test.A machine cannot make subjective decisions, so the team found a solution to objectify and quantify the dancers’ movements. “The eight Laban efforts are commonly used in theatre and dance classes to expand students’ creativity,” says Cecilia. “These are basic movements, including punching, wringing, and pressing, that a robot could easily identify.”From this information, Cecilia and Rui hope to develop a virtual dance partner that can make its own organic moves in time with a real-life dancer. “Inertial motion capture was the perfect choice for this type of research,” continues Rui. “We had a well-built model that was based on real movement, which provided a baseline for machine learning.”“The research project was incredibly enlightening on the importance of human connection,” concludes Cecilia. “Virtual dance partners are not currently able to replace real ones.” Small sensations, such as breaths and footsteps, are vital when dancing cohesively with a partner. At this stage of technology development, these nuances are not available digitally. However, that’s not to say it won’t happen in the future. Ghost Dance proved that in the future, this could be a feasible alternative to dancing with a real counterpart. It seems increasingly possible when using inertial motion capture to create the basis of the digital partner.Using Xsens meant that the dancers could perform freely, with no need to adjust choreography. This led to an optimal experience when dancing with a virtual partner. <img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1742888642787-Ghost+dance+Overlay+of+virtual+and+real+partners+dancing+3.png" style="width:100%px" class="fr-fic fr-dib" />

With Inertial Motion Capture

Ghost Dance: Building a virtual dance partner

This fresh, newly captured video from Unitree's testing grounds showcases the breakneck speed of humanoid intelligence advancement. Every day brings something thrilling!

This fresh, newly captured video from Unitree's testing grounds showcases the breakneck speed of humanoid intelligence advancement. Every day brings something thrilling!

Movement creates intelligence - Unitree's G1 humanoid robot nails the world's first kip-up!

One year after Unitree H1 (1.8m) pioneered the first standing backflip by an electric humanoid robot (March 2024). Meet the Unitree G1 – now flawlessly conquering an even more challenging standing side flip. (Zero malfunctions/damage occurred during programming and filming.)

One year after Unitree H1 (1.8m) pioneered the first standing backflip by an electric humanoid robot (March 2024). Meet the Unitree G1 – now flawlessly conquering an even more challenging standing side flip. (Zero malfunctions/damage occurred during programming and filming.)

World's First Side-Flipping Humanoid Robot: Unitree G1

The body regulates its metabolism precisely and continuously, with specialised cells in the pancreas constantly monitoring the amount of sugar in the blood, for example. When this blood sugar level increases after a meal, the body sets a signal cascade in motion in order to bring it back down.In people suffering from diabetes, this regulatory mechanism no longer works exactly as it should. Those affected therefore have too much sugar in their blood and need to measure their blood sugar level and inject themselves with insulin in order to regulate it. This is a relatively imprecise approach compared to the body’s own mechanism.<h2>Equipping cells with special functions</h2>Martin Fussenegger is Professor of Biotechnology and Bioengineering at the Department of Biosystems Science and Engineering of ETH Zurich in Basel. With the above situation in mind, he and his team have been working on cell therapies for some time. One day, the hope is that these therapies will allow metabolic diseases such as diabetes to be treated individually and precisely – or even cured.But how do these cell therapies work? First, the researchers modify human cells by incorporating a network of genes that give the cells special abilities. These cells are <a>implanted</a> under the skin, for example, and the network is activated by a specific external stimulus.<h2>A suitable switch is key</h2>To that end, the researchers have developed various types of switches over recent years. Some can be controlled electrically, others with light, and one even using music by the British rock band Queen (see <a href="https://ethz.ch/en/news-and-events/eth-news/news/2023/08/cells-with-an-ear-for-music-release-insulin.html">ETH News</a>).The researchers in Basel have now developed another variant, which they have presented in the journal <a href="https://doi.org/10.1038/s41551-025-01350-7">Nature Biomedical Engineering.</a>“For me, this solution is the best gene switch that my group and I have built so far,” says Fussenegger. The reason is that the switch can be triggered using the long-established active ingredient nitroglycerine, and that the means of application – sticking a patch to the skin – is very simple. Corresponding patches are already available to buy in various sizes in any pharmacy.Nitroglycerine quickly diffuses out of the patch and into the skin, where it encounters an implant that contains modified human kidney cells.<h2>Network activated by nitric oxide</h2>These cells specifically intercept the nitroglycerine and have a built-in enzyme that converts it into nitric oxide (NO), a natural signalling molecule. In the body, NO normally causes blood vessels to dilate, leading to increased blood flow. It is broken down within a few seconds and therefore only affects a very localised area.The implanted cells are modified so that NO triggers the production and release of the chemical messenger GLP-1, which in turn boosts insulin release by the beta cells of the pancreas and thus regulates blood sugar level. GLP-1 also triggers a feeling of satiety, thereby reducing food intake.The new switch is made exclusively of human constituents – that is, it contains no components from other species. “That’s a new and groundbreaking feature,” says Fussenegger. With components from other species, there is always a risk of false triggering, interference with the body’s own processes, or immune reactions. “Here, we’re able to rule that out.”<h2>A whole arsenal of switches</h2>In the last 20 years, the ETH professor has developed various different gene switches, some of which respond to physical triggers such as current, sound waves or light. Which type has the best chance of being implemented one day?“Physical triggers are interesting because we don’t need to use molecules that interfere with the body’s own processes,” the biotechnologist says. He explains that electrical signals are ideal for controlling switches and gene networks using portable electronics such as smartphones or smartwatches – and AI can then be incorporated, too. “I therefore think electrogenetic cell therapies have the best chances of implementation. In terms of chemical switches, I see the new solution as being in pole position,” says Fussenegger.However, the further development of these cell therapies based on gene switches is a complex and lengthy process. “Developing a cell therapy to market maturity not only takes decades but also requires lots of staff and sufficient resources,” says the researcher. “There’s no shortcut.”Until now, Fussenegger’s work has focused mainly on cell therapies for diabetes, which is one of the world’s most prevalent metabolic diseases, affecting one in ten people. “That’s the model disease we work with. Fundamentally, however, it’s also possible to develop cell therapies for other metabolic, autoimmune or even neurodegenerative diseases – in principle, for everything that requires dynamic regulation.” According to Fussenegger, many drugs are like a hammer that is used to strike at a problem blindly. “Cell therapies, on the other hand, solve the problem in a similar way to the body,” he says.<h2>Reference</h2>Mahameed M, Xue S, Danuser B, Charpin-El Hamri G, Xie M, Fussenegger M: Nitroglycerin-responsive gene switch for the on-demand production of therapeutic proteins, Nature Biomedical Engineering, 14 February 2025, doi: <a href="https://doi.org/10.1038/s41551-025-01350-7">external page10.1038/s41551-025-01350-7</a>

A skin patch with nitroglycerine is the switch that controls an implant underneath (symbolic image). (Image: Josef Kuster / ETH Zurich)

ETH researchers have developed a new gene switch that can be activated using a commercially available nitroglycerine patch applied to the skin. One day, researchers want to use switches of this kind to trigger cell therapies for various metabolic diseases.

A new switch for the cell therapies of the future

The use of robots alongside humans is increasing rapidly, making the flexibility of these machines an important safety feature. A robot's ability to adapt flexibly to its surroundings makes the difference between smooth operation and potential hazards, such as collisions with people nearby. The German Aerospace Center (Deutsche Zentrum für Luft- und Raumfahrt; DLR) has established itself as a pioneer in the field of cobots – collaborative robots that work in close cooperation with humans. Until now, the goal of cobot research has been to design robots that behave like a mechanical spring – if moved towards a desired position, they will always return to their original position. DLR researchers have now presented a more advanced concept in the journal Science Robotics. Their approach allows robots to yield without returning to their original position like a spring. This behaviour is similar to that of humans in joint practical tasks that need to be completed, where one person takes the lead while the other remains flexible and compliant.Michael Panzirsch, researcher at the DLR Institute of Robotics and Mechatronics, explains: "The new elasto-plastic approach makes human-robot collaboration much easier, as the robot can now clearly distinguish between its own programmed movements and external influences from the environment. The robot should only react plastically to the influence of the environment, meaning it should move out of the way and remain in that spot."In addition, the innovative controller generally simplifies interactions with objects that have a complex movement. For example, a hinged door can only be opened by rotating it around its axis. The robot follows the correct direction of movement – the circular motion around the hinges – almost automatically via the controller and without the need for an additional model of the door. This is comparable to a person opening a door with their eyes closed, simply pulling on the door handle and automatically adapting to the rotating motion in a plastically compliant manner.<img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1742345164286-image-1000-a8507f2c4983a98356706e6648326803.jpeg" />Two robotic hands cooperating to handle a tool While the arm of the DLR humanoid robot (right) independently carries an object, an astronaut controls the ESA Interact Rover's arm (left). The astronaut guides the object to the target position. The new approach allows for the humanoid to maintain the object's rotation while yielding to the rover arm during linear movements.  Credit: DLR (CC BY-NC-ND 3.0)<h2>Applications in space research and care</h2>The DLR Institute of Robotics and Mechatronics has been researching sensitive robots for decades. It has developed a robotic arm that stands out from conventional rigid industrial robots thanks to its remarkable flexibility. The elasto-plastic control approach was successfully tested in space as early as January 2024. The Surface Avatar project series is investigating the teleoperation of several robotic avatars on a planetary surface. The focus here is on the successful cooperation between a diverse team of robots performing collaborative tasks. "For the first time, our controller enabled cooperation between a rover from the European Space Agency's Human Robot Interaction Laboratory and a humanoid DLR robot controlled by an astronaut on the International Space Station," explains Neal Y. Lii, Scientific Director of the Surface Avatar programme.But the versatility of the technology is not limited to space. In the care sector, the elasto-plastic controller is proving to be a valuable aid. As part of the SMiLE project (Services for People with Living Conditions and Restrictions; Servicerobotik für Menschen in Lebenssituationen mit Einschränkungen), DLR researchers like Jörn Vogel are developing concepts for assistance systems designed to effectively support people with physical limitations and those in need of care in everyday life. The elasto-plastic controller not only facilitates cooperation between humans and robots but also enables the robot to seamlessly slip into an assistant role without requiring complex additional sensor technology.Advances in robotics, particularly in terms of compliance and adaptability, not only accelerate the integration of robots into everyday life but also increase safety and effectiveness. In a future where humans and machines work ever more closely together, it will be crucial for robots to not only react but also interpret our needs and idiosyncrasies, thereby mirroring human capabilities.

Remote-controlled from the ISS − DLR Rollin' Justin robot and the ESA Interact Rover. DLR's autonomous humanoid robot Rollin' Justin (right) and the ESA Interact Rover (left) being controlled from the International Space Station ISS. They are cooperating on the handling of a tool. Credit: DLR (CC BY-NC-ND 3.0)

DLR's concept allows collaborative robots to yield without being forced back to their original position like a mechanical spring.

The art of compliant robotics

<html><head></head><body>We move thanks to coordination among many skeletal muscle fibers, all twitching and pulling in sync. While some muscles align in one direction, others form intricate patterns, helping parts of the body move in multiple ways.In recent years, scientists and engineers have looked to muscles as potential actuators for “biohybrid” robots — machines powered by soft, artificially grown muscle fibers. Such bio-bots could squirm and wiggle through spaces where traditional machines cannot. For the most part, however, researchers have only been able to fabricate artificial muscle that pulls in one direction, limiting any robot’s range of motion.Now MIT engineers have developed a <a href="https://pubs.rsc.org/en/content/articlelanding/2025/bm/d4bm01017e" target="_blank">method to grow artificial muscle tissue</a> that twitches and flexes in multiple coordinated directions. As a demonstration, they grew an artificial, muscle-powered structure that pulls both concentrically and radially, much like how the iris in the human eye acts to dilate and constrict the pupil.The researchers fabricated the artificial iris using a new “stamping” approach they developed. First, they 3D-printed a small, handheld stamp patterned with microscopic grooves, each as small as a single cell. Then they pressed the stamp into a soft hydrogel and seeded the resulting grooves with real muscle cells. The cells grew along these grooves within the hydrogel, forming fibers. When the researchers stimulated the fibers, the muscle contracted in multiple directions, following the fibers’ orientation.“With the iris design, we believe we have demonstrated the first skeletal muscle-powered robot that generates force in more than one direction. That was uniquely enabled by this stamp approach,” says Ritu Raman, the Eugene Bell Career Development Professor of Tissue Engineering in MIT’s Department of Mechanical Engineering.The team says the stamp can be printed using tabletop 3D printers and fitted with different patterns of microscopic grooves. The stamp can be used to grow complex patterns of muscle — and potentially other types of biological tissues, such as neurons and heart cells — that look and act like their natural counterparts.“We want to make tissues that replicate the architectural complexity of real tissues,” Raman says. “To do that, you really need this kind of precision in your fabrication.”She and her colleagues <a href="https://pubs.rsc.org/en/content/articlelanding/2025/bm/d4bm01017e" target="_blank">published their open-access results Friday in the journal Biomaterials Science</a>. Her MIT co-authors include first author Tamara Rossy, Laura Schwendeman, Sonika Kohli, Maheera Bawa, and Pavankumar Umashankar, along with Roi Habba, Oren Tchaicheeyan, and Ayelet Lesman of Tel Aviv University in Israel.<img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1742260285838-MIT-MuscleStamp-02-press.jpg" style="width: 100%px;" class="fr-fic fr-dib">The researchers developed a new “stamping” approach. First, they 3D-printed a small, handheld stamp (top images) patterned with microscopic grooves, each as small as a single cell. Then they pressed the stamp into a soft hydrogel and seeded the resulting grooves with real muscle cells. The cells grew along these grooves within the hydrogel, forming fibers (bottom image). Image: Courtesy of the researchers<h2>Training space</h2>Raman’s lab at MIT aims to engineer biological materials that mimic the sensing, activity, and responsiveness of real tissues in the body. Broadly, her group seeks to apply these bioengineered materials in areas from medicine to machines. For instance, she is looking to fabricate artificial tissue that can restore function to people with neuromuscular injury. She is also exploring artificial muscles for use in soft robotics, such as muscle-powered swimmers that move through the water with fish-like flexibility.Raman has previously developed what could be seen as gym platforms and workout routines for lab-grown muscle cells. She and her colleagues designed a <a href="https://news.mit.edu/2023/wobbly-gel-mat-trains-muscle-cells-work-together-1020" target="_blank">hydrogel “mat”</a> that encourages muscle cells to grow and fuse into fibers without peeling away. She also derived a way to “exercise” the cells by genetically engineering them to twitch in response to pulses of light. And, her group has come up with ways to direct muscle cells to grow in long, parallel lines, similar to natural, striated muscles. However, it’s been a challenge, for her group and others, to design artificial muscle tissue that moves in multiple, predictable directions.“One of the cool things about natural muscle tissues is, they don’t just point in one direction. Take for instance, the circular musculature in our iris and around our trachea. And even within our arms and legs, muscle cells don’t point straight, but at an angle,” Raman notes. “Natural muscle has multiple orientations in the tissue, but we haven’t been able to replicate that in our engineered muscles.”<h2>Muscle blueprint</h2>In thinking of ways to grow multidirectional muscle tissue, the team hit on a surprisingly simple idea: stamps. Inspired in part by the classic Jell-O mold, the team looked to design a stamp, with microscopic patterns that could be imprinted into a hydrogel, similar to the muscle-training mats that the group has previously developed. The patterns of the imprinted mat could then serve as a roadmap along which muscle cells might follow and grow.“The idea is simple. But how do you make a stamp with features as small as a single cell? And how do you stamp something that’s super soft? This gel is much softer than Jell-O, and it’s something that’s really hard to cast, because it could tear really easily,” Raman says.The team tried variations on the stamp design and eventually landed on an approach that worked surprisingly well. The researchers fabricated a small, handheld stamp using high-precision printing facilities in MIT.nano, which enabled them to print intricate patterns of grooves, each about as wide as a single muscle cell, onto the bottom of the stamp. Before pressing the stamp into a hydrogel mat, they coated the bottom with a protein that helped the stamp imprint evenly into the gel and peel away without sticking or tearing.As a demonstration, the researchers printed a stamp with a pattern similar to the microscopic musculature in the human iris. The iris comprises a ring of muscle surrounding the pupil. This ring of muscle is made up of an inner circle of muscle fibers arranged concentrically, following a circular pattern, and an outer circle of fibers that stretch out radially, like the rays of the sun. &nbsp;Together, this complex architecture acts to constrict or dilate the pupil.Once Raman and her colleagues pressed the iris pattern into a hydrogel mat, they coated&nbsp;the mat with cells that they genetically engineered to respond to light. Within a day, the cells fell into the microscopic grooves and began to fuse into fibers, following the iris-like patterns and eventually growing into a whole muscle, with an architecture and size similar to a real iris.When the team stimulated the artificial iris with pulses of light, the muscle contracted in multiple directions, similar to the iris in the human eye. Raman notes that the team’s artificial iris is fabricated with skeletal muscle cells, which are involved in voluntary motion, whereas the muscle tissue in the real human iris is made up of smooth muscle cells, which are a type of involuntary muscle tissue. They chose to pattern skeletal muscle cells in an iris-like pattern to demonstrate the ability to fabricate complex, multidirectional muscle tissue.“In this work, we wanted to show we can use this stamp approach to make a ‘robot’ that can do things that previous muscle-powered robots can’t do,” Raman says. “We chose to work with skeletal muscle cells. But there’s nothing stopping you from doing this with any other cell type.”She notes that while the team used precision-printing techniques, the stamp design can also be made using conventional tabletop 3D printers. Going forward, she and her colleagues plan to apply the stamping method to other cell types, as well as explore different muscle architectures and ways to activate artificial, multidirectional muscle to do useful work.“Instead of using rigid actuators that are typical in underwater robots, if we can use soft biological robots, we can navigate and be much more energy-efficient, while also being completely biodegradable and sustainable,” Raman says. “That’s what we hope to build toward.”This work was supported, in part, by the U.S. Office of Naval Research, the U.S. Army Research Office, the U.S. National Science Foundation, and the U.S. National Institutes of Health.</body></html>

MIT engineers grew an artificial, muscle-powered structure that pulls both concentrically and radially, much like how the iris in the human eye acts to dilate and constrict the pupil. Image: Courtesy of the researchers

MIT engineers developed a way to grow artificial tissues that look and act like their natural counterparts.

Artificial muscle flexes in multiple directions, offering a path to soft, wiggly robots

<html><head></head><body>Unlock unlimited sports potential (Extra large joint movement space angle, 23~43 joints) Force control of dexterous hands, manipulation of all thingsImitation &amp; reinforcement learning driven Robot world model, let’s create it together Unitree G1 Price from $16K (Tax and Shipping cost excluded)More introduction:&nbsp;<a tabindex="0" href="https://www.youtube.com/redirect?event=video_description&amp;redir_token=QUFFLUhqbFpMZ0ZSV05IaDdTbEZuQnlFN1B3cDgzbnY0d3xBQ3Jtc0trTXhubEF2aWpndUhNLUFQajBBdmJObEFrRmZlcWdEdTN3dm1Fdzd0LUhGeVhxRF9HUUYwdl9NM2x5UnplTlYtR05zdkxSdUhvUk0zNktiWGhvdlpkNHhpazlUOVhpNHk5dmI3cEJRWWI2U3JQWEttTQ&amp;q=https%3A%2F%2Fwww.unitree.com%2Fg1&amp;v=GzX1qOIO1bE" rel="nofollow" target="_blank" data-immersive-translate-walked="fad7c807-08d6-4a00-ad03-0c3b7086529c">https://www.unitree.com/g1</a>Official Website: www.unitree.com&nbsp;Sales contact: sales_global@unitree.cc</body></html>

AI Avatar  Price from $16K

Unitree Introducing  Unitree G1 Humanoid Agent

720° Spin Kick - Hear the Impact! Kung Fu BOT Gameplay RAW. (No Speed-Up) (Do not imitate, please keep a safe distance from the machine)