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 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>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)

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)

Kungfu BOT GAME

We have continued to upgrade the Unitree G1's algorithm, enabling it to learn and perform virtually any movement. What other moves would you like to see. Do share with us in the comments. (Please keep a safe distance from the robot.)

We have continued to upgrade the Unitree G1's algorithm, enabling it to learn and perform virtually any movement.What other moves would you like to see. Do share with us in the comments. (Please keep a safe distance from the robot.)

Kungfu BOT: Unitree G1

<h2 data-immersive-translate-walked="05740628-8191-4ac2-95c7-00714c5fc3bf" id="isPasted" data-element-id="headingsMap-4-0">Keep the Music Going, Keep the Dance Flowing!</h2>Feature was just developed in the past few days and hasn't been rolled out to customers yet. There are also variations in functionality across different models and versions of the robot.

Feature was just developed in the past few days and hasn't been rolled out to customers yet. 


Keep the Music Going, Keep the Dance Flowing!

<h2 id="isPasted">What Dance Would You Like to Perform with Unitree G1?</h2>With the upgraded algorithm, G1 can learn any dance. Leave a comment to tell us what dance you'd like to see！

With the upgraded algorithm, G1 can learn any dance. Leave a comment to tell us what dance you'd like to see！

What Dance Would You Like to Perform with Unitree G1?

Hello everyone, let me introduce myself again. I am Unitree H1 "Fuxi".&nbsp;I am now a comedian at the Spring Festival Gala, hoping to bring joy to everyone.&nbsp;Let’s push boundaries every day and shape the future together.A little surprise: the handkerchief can not only spin but can also be thrown out and automatically returned to its position.<img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNzM4MDc3NzEzOTI3LeW+ruS/oeWbvueJh18yMDI1MDEyODIzMDMzNy5qcGciLCJlZGl0cyI6eyJyZXNpemUiOnsid2lkdGgiOjk1MCwiZml0IjoiY292ZXIifX19" style="width: 100%px;" class="fr-fic fr-dib">

Debut at the Spring Festival Gala

Unitree H1: Humanoid Robot Makes Its Debut at the Spring Festival Gala

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

Deep Reinforcement Learning

Unitree H1

Unitree G1 Bionic: Agile Upgrade

We’ve adapted motion capture data for Unitree H1, H1-2, and G1 humanoid robots, using numerical optimization methods to make their movement trajectories more natural.&nbsp;Open-Source：<a tabindex="0" href="https://www.youtube.com/redirect?event=video_description&redir_token=QUFFLUhqbnp6ZlVPN3FwdWRUQ0JISVV0emRpYlBfbkRpQXxBQ3Jtc0tuUEJPbGJ6d3pQUEFOUDJmRVMwcjdXNXZTbnp2TGIzbGhwcUlGcVdrOXBYS0JpMHU1R2RkVVJBS1dBcGVpZU9BXzJpd3N5OTEtSzcxSjh0MEdHZkZaa25fTENDMWMwaVNqNVJrRm9fX0xEdFRBeDFxOA&q=https%3A%2F%2Fhuggingface.co%2Fdatasets%2Funitreerobotics%2FLAFAN1_Retargeting_Dataset&v=SdZoEke0GPk" rel="nofollow" target="_blank">https://huggingface.co/datasets/unitr...</a>

We’ve adapted motion capture data for Unitree H1, H1-2, and G1 humanoid robots, using numerical optimization methods to make their movement trajectories more natural.

Unitree Humanoid Robots Updated With Open-Source Full-Body Motion Dataset

The humanoid robot driven by the robot AI world model unlocks many new skills!&nbsp;Strong power is waiting for you to develop!Breaking the full-size humanoid speed world record of 3.3m/s (the previous record was about 2.5m/s) Full body dynamic coordinated dance: Subject3&nbsp;Touch the height in place etc.&nbsp;More introduction: www.unitree.com/h1 <h2> </h2>

[full-size humanoid] Evolution V3.0

Unitree H1 Breaking humanoid robot speed world record

Embodied AI, Price below $90k Preview over half-a-year achievement The highest-power-performance robot of its counterparts with similar specifications in the world, weigh ~47Kg, maximum joint torque of 360N.m For more product information, please contact us through our official website:&nbsp;<a tabindex="0" href="https://www.youtube.com/redirect?event=video_description&redir_token=QUFFLUhqa2lqY1IxNDEyVl9UX1hYTHJLNjhMcVh0bk5Td3xBQ3Jtc0ttMW1hRjdha2NoQjVTYlZiTDhzTzlOQmZsYlY2QlpjSEhFOER1eHJ4UmxwejJGQlpRVXFzRXlwTzZiSDVQdFpLQWlpYUxTRk54QWJlQ2N2MEFQd2JxV3M2b3FDdlc1NWIyNlJBSmc3NGxLLU9INkdwcw&q=https%3A%2F%2Fwww.unitree.com%2Fh1&v=q8JMX6PGRoI" rel="nofollow" target="_blank">https://www.unitree.com/h1</a>

Price below $90k

Unitree General-pupose Humanoid Robot H1 Evolution V2.0

Researchers at the Italian Institute of Technology (IIT) are transforming human-robot collaboration with adaptive interfaces, enabling real-time robot adjustments and safe, seamless interactions.Key takeaways:<ul><li>Real-time adaptation for collaboration:&nbsp;Sirintuna and Ozdamar developed an adaptive collaborative interface (ACI) that allows robots to adjust their actions to the human movement intention in real-time, improving teamwork and efficiency.</li><li>Safety and predictability:&nbsp;Safety protocols and torque-controlled robots reduce risks in human-robot interaction, though unpredictable human behavior remains a challenge.</li><li>Xsens motion capture: The researchers use Xsens for precise, continuous movement data, crucial for interpreting human intentions and enabling seamless robot-human collaboration.</li><li>Future applications:&nbsp;The research has potential in healthcare, emergency response, and home assistance, aiming for robots that adapt intuitively in real-life, unstructured environments.&nbsp;</li></ul>Humans have been working with machines for centuries, and with the ongoing robotics revolution, this collaboration is becoming more equal. Researchers Doganay Sirintuna and Idil Ozdamar from the Italian Institute of Technology (IIT) are at the forefront of this change, investigating how robots can effectively work with humans in tasks such as carrying and delivering objects.&nbsp;The new challenge&nbsp;IIT has been actively researching human-robot collaboration for several years, showcasing robots that can perform a variety of tasks, from assisting in drilling holes to serving cups of coffee. &nbsp;Researchers Doganay Sirintuna and Idil Ozdamar, from the Human-Robot Interfaces and Interaction Laboratory, are developing a framework that allows robots to assist with transporting objects. Their framework, called Adaptive Collaborative Interface (ACI) uses haptic feedback and motion capture data to enable robots to adjust their speed and position for better teamwork with humans.&nbsp;In Ozdamar's study, “<a href="https://arxiv.org/abs/2209.14009" target="_blank" rel="noopener noreferrer">Carrying the Uncarriable: A Deformation-Agnostic and Human-Cooperative Framework for Unwieldy Objects Using Multiple Robots</a>,” a framework is presented for one person and two robots to carry a large, deformable object using flexible straps. In a related study by Sirintuna and Ozdamar, “<a href="https://arxiv.org/abs/2201.10392" target="_blank" rel="noopener noreferrer">Human-Robot Collaborative Carrying of Objects with Unknown Deformation Characteristics</a>,” they explore handling items from flexible ropes to rigid rods. By analyzing human movements and force feedback, robots can detect the deformability of the handled objects and adapt their actions. &nbsp;<iframe width="640" height="360" src="https://www.youtube.com/embed/Q3sA6YzTaaE?&amp;wmode=opaque&amp;enablejsapi=1&amp;origin=https://www.wevolver.com" frameborder="0" allowfullscreen="" class="fr-draggable" data-lf-form-tracking-inspected-kn9eq4roawkarlvp="true" data-lf-yt-playback-inspected-kn9eq4roawkarlvp="true" data-lf-vimeo-playback-inspected-kn9eq4roawkarlvp="true"></iframe>Sirintuna and Ozdamar's research focuses on robots consisting of a base with wheels (mobile manipulators) and a robotic arm with multiple joints (known as collaborative robots or cobots). They explain, "In our setup, we have 9° of freedom, and with wheeled robots, you can perform fast movements. So, we selected an industrial robot to concentrate on collaboration tasks."&nbsp;The choice of Xsens &nbsp;In their work, Sirintuna and Ozdamar rely heavily on <a href="https://www.movella.com/products/motion-capture" target="_blank" rel="noopener noreferrer">Xsens motion capture</a> to collect accurate movement data to guide the robots. Xsens allows the researchers to conduct the experiments with minimal setup—making it a practical choice for laboratory environment. Sirintuna and Ozdamar stress the importance of precise, continuous data when working in close collaboration with humans. They appreciate Xsens’ reliability, noting, “We used Xsens because its data was very continuous, which allowed us to provide a reliable stream of data for the human-robot collaboration. Optical sensors we have tried can experience jumps in position, affecting the performance of our framework.”&nbsp;A key focus of their research is interpreting human intentions through movement data. Xsens provides detailed kinematic data, enabling them to categorize actions such as standing still, pushing, or pulling. Through repeated training, they achieved a 98% accuracy in predicting human movements within just three months. “We label specific joint positions and angles as pushing or pulling and use these as input for our system,” Ozdamar explains. Sirintuna and Ozdamar also developed an algorithm that interprets human’s rotational intent by analyzing torso and hand movements, with the goal of creating robots that assist efficiently in tasks like turning while carrying objects. &nbsp;The research results &nbsp; As a result of applying the adaptive collaborative interface, Sirintuna and Ozdamar found that cobots can handle tasks with higher precision, anticipating human movements in real time and adjusting actions based on nuanced data. With the help of a robot operating under ACI in the research on the different deformable objects, "participants completed the task faster, with less effort and higher effectiveness". In the research with two robots assisting one person with transporting a bulky object using deformable straps, the ACI allowed robots to have faster response and better alignment of the movement and required a lesser force input from the person, making the lifting task easier.&nbsp;The findings underscore the power of applying ACI for human-robot collaboration scenarios and lay a foundation for future research in this area.&nbsp;<iframe width="640" height="360" src="https://www.youtube.com/embed/ounQmCdYlC4?&amp;wmode=opaque&amp;enablejsapi=1&amp;origin=https://www.wevolver.com" frameborder="0" allowfullscreen="" class="fr-draggable" data-lf-form-tracking-inspected-kn9eq4roawkarlvp="true" data-lf-yt-playback-inspected-kn9eq4roawkarlvp="true" data-lf-vimeo-playback-inspected-kn9eq4roawkarlvp="true"></iframe> The future of human-robot collaboration and humanoids&nbsp;Looking ahead, Sirintuna and Ozdamar see their research supporting applications in healthcare, emergency response, and home assistance, as well as enabling robots to become common in public spaces and workplaces to meet needs, for example, in agriculture, affected by climate change. The researchers note that “human-robot teams that leverage human adaptability and decision-making can perform tasks with the flexibility required in unstructured environments.”&nbsp;However, making this robotized future reality requires addressing safety concerns in human-robot collaboration. The research robots are torque-controlled, equipped with soft joints, and programmed to avoid reacting to unexpected high-velocity impacts or large force inputs. Yet, as the researchers point out, for real-world applications, the unpredictability of human behavior remains the greatest challenge. “We design algorithms based on expected movements, but humans often behave in unexpected ways,” says Sirintuna. Ozdamar adds, “We can ensure slightly more safety on the robots’ side than on a person’s because we can predict the robot’s behavior.”&nbsp;Ultimately, Sirintuna and Ozdamar’s work lays a foundation for future robots capable of safe, intuitive collaboration with humans, bringing us closer to a world where robots seamlessly assist in our daily lives.&nbsp;