Unitree B2 continues to evolve every day with the acceleration of AI. Is there a limit to its evolution? More introduction: www.unitree.com/b2The fastest industrial quadruped robot with a speed of 6m/s.Excellent terrain adaptability, ensuring stable driving on slippery or uneven surfaces.Excellent continuous stair climbing ability, easy to handle steps.170% increase in joint performance with 360 N.m of torque. Extreme performance provids greater flexibility and stability for industrial operations.Overcoming obstacles. Stable and tough. Superior obstacle-crossing ability, easy to cross the mess of wood piles, 40cm high platforms and other obstacles.100% increase in sustained load 200% increase in endurance.

Unitree B2 continues to evolve every day with the acceleration of AI. Is there a limit to its evolution?

Unitree B2 has evolved once again, is there an end?

Point rate 64000 points/s&nbsp;Distance resolution 4.5mm&nbsp;FOV 360°x96°&nbsp;Scan distance 30m&nbsp;Performance increased by 200%&nbsp;Open source address: <a dir="ltr" href="https://t.co/u1Hr2wB1T2" rel="noopener noreferrer nofollow" target="_blank" id="isPasted">https://github.com/unitreerobotics/point_lio_unilidar…</a>

New Upgrade Released: 200% Increase in L2 4D LiDAR Performance $419 🥳


New Upgrade Released: L2 4D LiDAR Doubles Performance for 419 USD

<article data-clipboard-cangjie='["root",{},["p",{},["span",{"data-type":"text"},["span",{"fonts":{"ascii":"微软雅黑","cs":"微软雅黑","eastAsia":"微软雅黑","hAnsi":"微软雅黑","hint":"eastAsia"},"data-type":"leaf"},"G1 has flexible mechanical dimensions and joint design, including 23-43 degrees of freedom, industrial-grade crossed roller bearings and low-inertia high-speed motors, providing powerful joint output. The maximum torque of the knee joint can reach 120N.m, the maximum load of the arm is about 3Kg, it has a large joint movement space, and is equipped with depth cameras, 3D lidar, 4-microphone array and other perception sensors, as well as an 8-core high-performance CPU. In addition, G1 also provides high computing power modules, smart batteries, chargers and other supporting equipment, supports smart OTA upgrades and secondary development, and is suitable for general humanoids, industry applications, fitness and embodied smart communities and other fields. It is worth mentioning that the price of the G1 bipedal humanoid robot independently developed by Unitree Robotics has been reduced to less than 100,000 for the first time, providing more companies and individuals with the opportunity to contact and apply humanoid robots. "]]]]' id="isPasted">G1 has flexible mechanical dimensions and joint design, including 23-43 degrees of freedom, industrial-grade crossed roller bearings and low-inertia high-speed motors, providing powerful joint output. The maximum torque of the knee joint can reach 120N.m, the maximum load of the arm is about 3Kg, it has a large joint movement space, and is equipped with depth cameras, 3D lidar, 4-microphone array and other perception sensors, as well as an 8-core high-performance CPU.&nbsp;</article>

AI-driven robots need to learn new actions as fast as possible. This is very important.

Learning in 2 Days, Human-Like Natural Walking

Continuously promote the implementation of industry applications to the ground Unitree B2 beyond the limit Maximum speed of 6m/s, sustained load of 40kg and sustained walking endurance of 5h. The comprehensive performance is two to three times that of existing quadruped robots worldwide! Adaptable to all terrains, large load, long-lasting endurance, and super athletic performance! Evolve, evolve, and evolve again! More introduction: www.unitree.com/en/b2 <h2> </h2>

Continuously promote the implementation of industry applications to the ground Unitree B2 beyond the limit Maximum speed of 6m/s, sustained load of 40kg and sustained walking endurance of 5h. The comprehensive performance is two to three times that of existing quadruped robots worldwide! 

Unitree releases B2, beyond the limits of hyper-evolution

The G1 robot can perform a standing long jump of up to 1.4 meters, possibly the longest jump ever achieved by a humanoid robot of its size in the world, standing only 1.32 meters tall; This video showcases some of the new features of the Go2 robot dog, which were updated a while ago but may still be unfamiliar to you. (Note: features vary by model and version) We sincerely hope you find it interesting!

The G1 robot can perform a standing long jump of up to 1.4 meters, possibly the longest jump ever achieved by a humanoid robot of its size in the world, standing only 1.32 meters tall.

Did you exercise today? Breaking Records! G1 Humanoid Robot Achieves a Jump Distance and Height Ratio of Over 1!

In the international Cybathlon competition, people with physical disabilities undertake routine tasks with the aid of assistive technology that can be seamlessly integrated into everyday life. Below, we present three ETH teams that will be putting their innovative solutions to the test at this October’s event.<h2 id="isPasted">Help from a fourlegged friend</h2>Developed by the Robotics Systems Lab at ETH&nbsp;Zur­ich, ALMA is a quadrupedal robot equipped with a range of sensors and a robotic arm. Unlike other entries in the Cybathlon discipline for assistive robots, all of which are attached to a wheelchair, ALMA moves autonomously on its own four legs, controlled by paraplegic pilot Sammy Kunz via a quadstick – a type of mouth-operated joystick. Deploying the robot as a separate system provides greater mobility, say team managers Carmen Scheidemann and Andrei Cramariuc. “But our biggest asset is also our biggest liability,” Scheidemann explains. “Because we have to ensure that ALMA moves safely without bumping into any objects.” In competition, the team has ten minutes to complete ten everyday tasks. For example, the pilot must use the robot to open a door and then close it behind them, or to pick up an apple and hold it in such a way that the pilot can take a bite. The quadstick used with ALMA features various tubes. By blowing or sucking, the pilot is able to control the different axes of the robot: either its quadrupedal platform or its gripping arm.“At a preliminary event in February, we had eight minutes to complete four tasks,” says Scheidemann. “In the end, we needed just over six.” The team is therefore confident about achieving a good score at the upcoming championship. In preparation for October’s event, various refinements to ALMA have been made in close cooperation with Kunz. Most of these involved enhancing the controls so that Kunz can operate the robot with as little practice as possible. “We suggest an improvement, and Sammy gives us feedback on what works for him and what doesn’t,” explains Scheidemann. “Then we make the necessary modifications.” Whereas 15 hours of practice were required before the preliminary event in February, improvements to the control system have now drastically reduced preparation times.Both managers have hugely enjoyed working with Kunz. “It’s really fulfilling to be working on a project that has the potential to bring about such a major improvement in the day-to-day lives of people with disabilities,” says Cramariuc. ANYmal robots, which provide the quadrupedal platform for ALMA, are already in use for a variety of industrial jobs, including the inspection of oil rigs. The current challenge is to deploy assistive robots not only in controlled envir­onments but also in everyday situations. The team will continue to refine ALMA. “But it will be a good few years before the platform is ready for market,” Scheidemann cautions. “We’re still very much at the experimental stage.”<a href="https://cybathlon.ethz.ch/en/teams/rsl" target="_blank" id="isPasted">To the RSL team</a><h2 id="isPasted">Cameras and a vibrating belt</h2>Pressing the right doorbell, finding a free seat and navigating an area containing obstacles of various heights are just some of the challenges that blind pilot Lukas Hendry will face in the Vision Assist­ance Race at the Cybathlon. Technical support comes from the Sight Guide team, which will guide Hendry using data from two cameras strapped to his chest. Patrick Pfreundschuh, one of the team managers, describes how the technology works: “We use one camera for positioning – that is, to tell us where Lukas is and where he’s heading. The other is a depth camera that takes 3D measurements of the surrounding area.” There’s also a third camera which the pilot holds in his hand to assist with tasks that require objects to be examined in more detail. All three cameras transmit information to a small, lightweight computer that Hendry carries on his back. The computer crunches the data and sends Hendry corresponding instructions via an audio signal. Finding a system with enough computing power was surprisingly difficult, says Pfreundschuh: “When your pilot is in the race, you need to be processing the input as quickly as possible. Otherwise, he might collide with an obstacle, which is obviously something we want to avoid!” The Sight Guide team is hopeful about making further improvements before the Cybathlon, such as making the audio signals that convey the instructions more easily understandable. In addition to the computer and cameras, Hendry also wears a special vibrating belt that tells him in which direction to move. “We don’t want to say exactly how this belt works, because it’s what gives us our competitive edge!” says Pfreundschuh with a smile.The Sight Guide team consists of doctoral candidates and students from the Autonomous Systems Lab at ETH Zurich, the Robotics and Perception Group at the University of Zurich and the Institute for Mechatronic Systems at Zurich University of Applied Sciences (ZHAW). For the doctoral students, the Cybathlon is both inspiring and enjoyable, which is why they are happy to work on the project in their spare time. Every month or two, they meet up with Hendry to perform mock-ups of the tasks they will face in the Cybathlon. Hendry then supplies feedback – for example, on how fast he receives the instructions – and many of the tweaks he suggests can be applied on the spot. Working with the pilot is one of the things that makes this project so special, says Pfreundschuh: “It’s great to see Lukas sailing through tasks that would be impossible for him without our technology. It makes me happy and proud to see the benefits we can provide for blind people simply by putting theory into practice.” The goal is to continue improving the technology once the Cybathlon is over – and Pfreundschuh hopes to find a new generation of students willing to take the reins.<a href="https://sightguide.tech/" target="_blank" id="isPasted">To the sightguide team</a><h2 id="isPasted">Sensing the ground while wearing prosthesis</h2>A key drawback of a prosthetic leg is that wearers are unable to feel the ground beneath their foot. The absence of sensory feedback on where their foot is positioned and how firmly it is touching the floor makes it difficult to walk, especially on uneven terrain or when climbing stairs. This is the main reason many patients decide against a prosthesis. But it doesn’t have to be this way, as Stefan Poth has discovered since becoming a pilot in the Cybathlon. He is taking part in the competition with his own prosthetic leg, which has been fitted with a special insole in the shoe. Developed by the NeuroLegs team, this insole is equipped with sensors that gather information on what the researchers call the foot-ground interaction. This includes feedback on whether Poth’s weight is on the toe, middle part or heel of his prosthetic foot. Data on where he is stepping is sent to a microprocessor attached to his waist. The computer processes the data and converts it into electrical stimulation by activating electrodes on an elastic belt that Poth wears around his leg stump. “Depending on where Stefan is stepping, electrical stimulation is applied in real time to either the front, side or back of the stump to replicate the sensation that would normally be perceived in the foot,” says Noemi Gozzi, co-manager of the NeuroLegs team.Poth’s team for the leg prosthesis race is made up of students from the Neuroengineering Lab at ETH Zurich. Affiliated with the Department of Health Sciences and Technology, the lab is headed by ETH professor Stanisa Raspopovic. This year’s team is building on the valuable experience gained in the previous Cybathlon four years ago. “Instead of starting from scratch, we’ve actually been able to improve our technology this year. For example, we’ve made it a lot more user­friendly,” says Valerio Aurucci, the second of the team’s two managers. The belt Poth wears around his leg stump was developed by this year’s team to avoid having to attach electrodes to his skin one by one, which has also made the system more reliable.Gozzi emphasises how rewarding it is to see their research being put into practice: “We’re trying to develop systems that will make people’s day-to-day lives easier. Stefan’s reaction when he felt a sensation from his foot for the first time was something very special – and it certainly made up for all those hours in the lab!” The Neuroengineering Lab is one of the leading research groups working on peripheral nerve stimulation, and Aurucci sees major benefits in the innovative solution they have developed: “The biggest advantage is that our system can be used with any prosthesis.” Getting to a market-ready product will require more development and additional safety features. The two team managers – both of whom are doing their doctorate at ETH – are therefore carefully considering their next step. Should they stick to research and hand over NeuroLegs to the next generation, or take the plunge into business by setting up a spin-off? The future is theirs to decide.<a target="_blank"></a><a href="https://cybathlon.ethz.ch/en/teams/neuro-legs" target="_blank">To the NeuroLegs team</a>

Helping to open doors: Cybathlon pilot Sammy Kunz uses his mouth to steer the assistance robot, while Carmen Scheidemann from the Robotics Systems Lab monitors the test run. Come October, the pressure will be on. (Photograph: Markus Bertschi / ETH Zurich)

In the international Cybathlon competition, people with physical disabilities undertake routine tasks with the aid of assistive tech that can be seamlessly integrated into everyday life. Here are three ETH teams that will be putting their innovative solutions to the test at this October’s event.

How four-legged robots and smart belts help people overcome everyday barriers

An ITMO PhD student has devised a way to design flexible robots capable of withstanding a shock load, retaining its energy, and adapting to movement on rough surfaces. The new robot’s joints are connected by flexible hinges rather than turning kinematic pairs. With such mechanisms, it’s possible to increase the capabilities of robots that interact with their environments: quadrupeds, anthropomorphic robots, and collaborative manipulators. The new <a href="https://www.researchgate.net/publication/383819099_Parametric_Synthesis_of_Compliant_Joints_for_Impact-Robust_Shaftless_Leg_Mechanisms" target="_blank" id="isPasted">design</a> will be unveiled at the International Conference on Intelligent Robots and Systems (IROS 2024).Roboticists from ITMO’s <a href="https://sai.itmo.ru/" target="_blank">Research Center “Strong AI in Industry”</a> have devised a method of optimizing a robot’s mechanical structure and movement trajectory to provide the necessary dynamic behavior. In order to test the method, ITMO PhD student&nbsp;Egor Rakshin&nbsp;has assembled a robot with flexible joints – its improved mechanism is impact-robust and can function even with insufficient information about its environment.&nbsp;When assembling the new model, the researchers used the one previously <a href="https://news.itmo.ru/en/news/13232/" target="_blank">developed</a> under the supervision of Prof. Ivan Borisov from ITMO’s Faculty of Control Systems and Robotics. In the previous version, mobility was provided by bearings, making the structure more rigid and less mobile; during a fall, part of the impact energy was dissipated through plastic deformation of the solid links.In the new version, the authors moved away from turning kinematic pairs with bearings in favor of flexible joints – they function as a passive suspension that absorbs the entire impact during the robot’s fall and protects drive gearboxes and rigid links from deformation. Additionally, the new design allows for recuperation, that is, recovering part of the energy dissipated during impact, as well as softening peak shock loads on the drives. Thanks to this, it may be possible to lower the requirements for the robot’s components and increase its energy efficiency.<img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1727134897715-1392501.jpg" style="width: 100%px;" class="fr-fic fr-dib">A prototype of the robot. The researchers have optimized its mechanism using global optimization genetic algorithms, then used 3D printing and laser cutting to print parts of the robot – and assembled the prototype. Next, they tested the robot using motion capture to compare its actual activity with one predicted by a model. Images courtesy of the researchersIn order to test the mechanism’s capacity to absorb shock loads, the researchers threw the robot from a meter’s height and hit it with a football. None of these impacts caused harm: during a fall, the robot “bounced” off the floor and continued its movement undisturbed.<blockquote>“Our robot performs well under shock loads and can function in unstructured environments – even on unknown terrain, moving blindly. Thanks to its flexible joints, the structure can move along rough surfaces without a complex feedback system. With this design approach, we will be able to extend the endurance of walking robots and manipulators that have to interact with environments to perform their functions. Currently, the mechanism is a prototype of a single leg that can be used to assemble a quadruped (for example, a robotic cheetah) capable of covering longer distances thanks to energy recuperation,” shares the paper’s first author Egor Rakshin, a PhD student and engineer at ITMO’s <a href="https://news.itmo.ru/en/search/?search=Laboratory+of+Biomechatronics+and+Energy-Efficient+Robotics" target="_blank">Laboratory of Biomechatronics and Energy-Efficient Robotics</a>.&nbsp;</blockquote><img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1727134923446-1392503.jpg" style="width: 100%px;" class="fr-fic fr-dib">A prototype of the robot. Image courtesy of the researchersIn the future, the researchers are planning to use the new method to create new robots (quadrupeds, bipeds, and hybrid locomotion robots), including those for logistics and industrial inspection.&nbsp;The talk&nbsp;<a href="https://iros2024-abudhabi.org/accepted-papers" target="_blank">Parametric Synthesis of Compliant Joints for Impact-Robust Shaftless Leg Mechanisms</a> will be delivered for the first time at&nbsp;<a href="https://iros2024-abudhabi.org/" target="_blank">IROS 2024</a>, a major robotics conference organized since 1988.1,587 presentations from all over the world will be held at the conference, including three from ITMO’s Faculty of Control Systems and Robotics, thus making the total of 12 IROS-accepted works by ITMO researchers over the years (in 2016, 2019, 2021, 2023, and 2024).IROS is&nbsp;<a href="https://portal.core.edu.au/conf-ranks/?search=IROS&by=all&source=all&sort=dsource&page=1" target="_blank">included</a> in the CORE conference ranking, where it is ranked A (one of the most prestigious positions). In 2024, the event will be held in Abu Dhabi on October 14-18. IROS aims to introduce the international community of robotics researchers to the latest cutting-edge findings in intelligent robots and machines.

Egor Rakshin. Photo courtesy of the subject

An ITMO PhD student has devised a way to design flexible robots capable of withstanding a shock load, retaining its energy, and adapting to movement on rough surfaces. The new robot’s joints are connected by flexible hinges rather than turning kinematic pairs.

Researchers Create Robots That Withstand Shock Loads

Recently, Zhejiang Province in east China carried out a comprehensive emergency response drill "Emergency Mission 2024" to strengthen its capabilities in responding to natural disasters. During this drill, a certain fire brigade collaborated with DEEP Robotics to provide a "quadruped robot hazard rescue solution." The robot dog, in coordination with drones, successfully completed the task of scouting for chemical explosion hazards. <img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1717404273023-%E5%9B%BE%E7%89%871.jpg" style="width: 100%px;" class="fr-fic fr-dib">Quadruped robots possess superior terrain adaptability. In the "Emergency Mission 2024" drill, the DEEP Robotics X30 robot dog was able to quickly traverse complex terrains and reach disaster sites promptly. <img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1717404325553-%E5%9B%BE%E7%89%872.jpg" style="width: 100%px;" class="fr-fic fr-dib">At the drill site, heavy rain caused severe flooding, leading to a factory explosion that ignited a warehouse containing oil and hazardous chemicals. The fire spread, threatening major hazardous chemical sources within the factory. The robot dog, in collaboration with drones, conducted comprehensive detection. Equipped with a dual-lens gimbal and gas detectors, it gathered crucial information on fire temperature, radiant heat intensity, toxic and harmful gases, and obstacles, providing valuable data to rescue personnel. DEEP Robotics is a leader in the innovation and application of embodied intelligence technology, being the first in the world to achieve collaborative search and rescue with robot dog clusters. In 2022, DEEP Robotics developed the "quadruped robot hazard rescue solution," which integrates hazard detection modules for flexible unmanned detection and search and rescue operations in post-earthquake rubble, indoor areas of collapsing buildings, tunnel traffic accidents, chemical pollution, and harsh environments such as toxic, hypoxic, and smoke-filled conditions following fires. <img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1717404358405-%E5%9B%BE%E7%89%873.jpg" style="width: 100%px;" class="fr-fic fr-dib">The DEEP Robotics X30 robot dog, the core of the solution, weighs 50 kilograms and can carry up to 85 kilograms under extreme conditions. It is IP67 rated for water and dust resistance and can operate in temperatures ranging from -20°C to 55°C, making it reliable in extreme cold and heat, as well as adverse weather conditions. In emergency rescue and detection missions, time is of the essence. The X30 robot dog’s unique fusion perception capability enables it to act swiftly even in the dark. It is reported that DEEP Robotics is advancing the "AI+ Plan" in a new round of technological innovation. By using new AI and software systems, along with extensive data, the robot dogs undergo self-learning training, breaking the limitations of traditional models and achieving extreme motion capabilities in complex and harsh environments. In the future, the "AI+ Plan" will also extend to perception, planning, decision-making, and human-machine interaction capabilities.

DEEP Robotics is a leader in the innovation and application of embodied intelligence technology, being the first in the world to achieve collaborative search and rescue with robot dog clusters.

Emergency Mission 2024: DEEP Robotics' Robot Dog Scouts for Fire and Explosion Hazards

Parents spend roughly 300 hours each year cleaning up after their kids. That’s nearly two weeks that could be otherwise spent doing, well, anything else. Researchers in Carnegie Mellon University’s <a href="https://www.meche.engineering.cmu.edu/index.html" rel="noopener" target="_blank" id="isPasted">Department of Mechanical Engineering</a>, in collaboration with Google DeepMind and the University of Washington, are hopeful that parents will regain tidying time and then some with <a href="https://linchangyi1.github.io/LocoMan/" rel="noopener" target="_blank">LocoMan</a>, a four-legged version of the Jetsons’ beloved maid “Rosey the Robot,” that could lend a hand in the not-so-distant future.<iframe width="640" height="360" src="https://www.youtube.com/embed/d-GLiRPiHIE?&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">&nbsp;&nbsp;&nbsp;</iframe>Quadrupedal robots, designed to move on four legs much like a dog, are already found leading search and rescue missions, surveying construction sites, and moving parts around factories. Their ability to navigate complex environments with a low center of gravity and light weight make quadrupedal robots a top contender for household use, too. Until now, the missing piece was the dexterity and versatility skills necessary for them to be efficient in daily life.By installing two custom-designed, lightweight manipulators (think robot arms) onto the front legs of a quadrupedal robot, <a href="https://engineering.cmu.edu/directory/bios/zhao-ding.html" target="_blank">Ding Zhao</a> has created a robot versatile enough to open doors, pour drinks, plug a phone in to charge, and—perhaps best of all—clean up after your on-the-go toddlers.<blockquote>While many researchers work on humanoid robots that look like humans, with potential to directly learn from humans or even replace humans in some tasks, we focus on robots that are complementary to humans to team up with them.<cite>Ding Zhao, Associate Professor, Mechanical Engineering</cite></blockquote>“While many researcher work on humanoid robots that look like humans, with potential to directly learn from humans or even replace humans in some tasks, we focus on robots that are complementary to humans to team up with them,” said Zhao, associate professor of mechanical engineering.Unlike humanoid robots that come at a high cost and hefty weight, Zhao’s manipulators can be added to existing lower-cost quadrupedal robots and are compact, lightweight, and easy to fabricate, making them an accessible technology.<img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNzE1NzM1MTQ3ODg3LTA1MDktZW0taG9tZS1oZWxwZXItcm9ib3QucG5nIiwiZWRpdHMiOnsicmVzaXplIjp7IndpZHRoIjo5NTAsImZpdCI6ImNvdmVyIn19fQ==" style="width: 100%px;" class="fr-fic fr-dib">The core idea is to leverage the leg as an integral component of the “robotic arm” for executing 6D pose manipulation.“We used four commercially available servos and 3D printed a few other parts to bring them to life,” Changyi Lin, a Ph.D. candidate in the CMU Safe AI Lab and the first author of the paper explained.Zhao’s team introduced the robot to a class of five preschool students at The Cyert Center for Early Education. After explaining to children how robots work and what we use them for, the children had the opportunity to interact with Zhao’s robot. The students were impressed with the robot’s capabilities and didn’t want it to leave their classroom.<img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNzE1NzM1MTc3MDc1LTA1MTMtZW0yLWhvbWUtaGVscGVyLXJvYm90LnBuZyIsImVkaXRzIjp7InJlc2l6ZSI6eyJ3aWR0aCI6OTUwLCJmaXQiOiJjb3ZlciJ9fX0=" style="width: 100%px;" class="fr-fic fr-dib">Ding Zhao (center), with children from the Cyert Center, interacting with the home-helper robot.The group continues to develop LocoMan to perform tasks autonomously by integrating advanced perception and intelligence planning capabilities into its existing whole-body controller.“We anticipate that robots like LocoMan will be ready to help out at home, or in daycares, within the next three years,” said Zhao. “It is a pleasant job just to imagine that I may no longer need to handle my kids’ messy fun.”This work will be presented at the loco-manipulation workshop and the manipulation skills workshop of the 2024 IEEE International Conference on Robotics and Automation.

New locomotion and manipulation technology from Ding Zhao’s lab will enable four-legged robots to lend a hand in the not-so-distant future.

Manipulation technology makes home-helper robot possible

<img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1715299294035-5712x4284.jpg" style="width: 100%px;" class="fr-fic fr-dib">The robot spontaneously changed its gait to cross a terrain with gaps. 2024 EPFL/BioRob-CC-BY-SA 4.0With the help of a form of machine learning called deep reinforcement learning (DRL), the EPFL robot notably learned to transition from trotting to pronking – a leaping, arch-backed gait used by animals like springbok and gazelles – to navigate a challenging terrain with gaps ranging from 14-30cm. The study, led by the&nbsp;<a href="https://www.epfl.ch/labs/biorob/" target="_blank">BioRobotics Laboratory</a> in EPFL’s School of Engineering, offers new insights into why and how such gait transitions occur in animals. “Previous research has introduced energy efficiency and musculoskeletal injury avoidance as the two main explanations for gait transitions. More recently, biologists have argued that stability on flat terrain could be more important. But animal and robotic experiments have shown that these hypotheses are not always valid, especially on uneven ground,” says PhD student Milad Shafiee, first author on a paper published in <a href="https://www.nature.com/articles/s41467-024-47443-w" target="_blank" rel="noopener">Nature Communications</a>.Shafiee and co-authors Guillaume Bellegarda and BioRobotics Lab head Auke Ijspeert were therefore interested in a new hypothesis for why gait transitions occur: viability, or fall avoidance. To test this hypothesis, they used DRL to train a quadruped robot to cross various terrains. On flat terrain, they found that different gaits showed different levels of robustness against random pushes, and that the robot switched from a walk to a trot to maintain viability, just as quadruped animals do when they accelerate. And when confronted with successive gaps in the experimental surface, the robot spontaneously switched from trotting to pronking to avoid falls. Moreover, viability was the only factor that was improved by such gait transitions.“We showed that on flat terrain and challenging discrete terrain, viability leads to the emergence of gait transitions, but that energy efficiency is not necessarily improved,” Shafiee explains. “It seems that energy efficiency, which was previously thought to be a driver of such transitions, may be more of a consequence. When an animal is navigating challenging terrain, it’s likely that its first priority is not falling, followed by energy efficiency.”<img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1715299423668-ezgif-3-e8b7f9ed78.jpg" style="width: 100%px;" class="fr-fic fr-dib">Guillaume Bellegarda, Milad Shafiee and Auke Ijspeert. 2024 EPFL/Jamani Caillet - CC-BY-SA 4.0<h2>A bio-inspired learning architecture</h2>To model locomotion control in their robot, the researchers considered the three interacting elements that drive animal movement: the brain, the spinal cord, and sensory feedback from the body. They used DRL to train a neural network to imitate the spinal cord’s transmission of brain signals to the body as the robot crossed an experimental terrain. Then, the team assigned different weights to three possible learning goals: energy efficiency, force reduction, and viability. A series of computer simulations revealed that of these three goals, viability was the only one that prompted the robot to automatically – without instruction from the scientists – change its gait.The team emphasizes that these observations represent the first learning-based locomotion framework in which gait transitions emerge spontaneously during the learning process, as well as the most dynamic crossing of such large consecutive gaps for a quadrupedal robot.“Our bio-inspired learning architecture demonstrated state-of-the-art quadruped robot agility on the challenging terrain,” Shafiee says.The researchers aim to expand on their work with additional experiments that place different types of robots in a wider variety of challenging environments. In addition to further elucidating animal locomotion, they hope that ultimately, their work will enable the more widespread use of robots for biological research, reducing reliance on animal models and the associated ethics concerns.<hr>ReferencesShafiee, M., Bellegarda, G. &amp; Ijspeert, A. Viability leads to the emergence of gait transitions in learning agile quadrupedal locomotion on challenging terrains. Nat Commun 15, 3073 (2024). <a href="https://doi.org/10.1038/s41467-024-47443-w" target="_blank" rel="noopener">https://doi.org/10.1038/s41467-024-47443-w</a>

Guillaume Bellegarda, Milad Shafiee and Auke Ijspeert. 2024 EPFL/Jamani Caillet - CC-BY-SA 4.0

A four-legged robot trained with machine learning by EPFL researchers has learned to avoid falls by spontaneously switching between walking, trotting, and pronking – a milestone for roboticists as well as biologists interested in animal locomotion.

Trotting robots reveal emergence of animal gait transitions

This story by Landon Hall was first published in the&nbsp;<a href="https://viterbischool.usc.edu/news/2024/04/teaching-robots-to-walk-on-the-moon-and-maybe-rescue-one-another/" target="_blank">USC Viterbi School of Engineering newsroom</a>.Georgia Tech alumna&nbsp;Feifei Qian&nbsp;(M.S. PHYS 2011, Ph.D. ECE 2015), an assistant professor of electrical and computer engineering at the USC Viterbi School of Engineering and School of Advanced Computing, leads the NASA LASSIE project alongside co-investigator&nbsp;Frances Rivera-Hernández, an assistant professor in the School of Earth and Atmospheric Sciences at Georgia Tech.&nbsp;Sharissa Thompson, a graduate student at Georgia Tech, is a student intern on the NASA Curiosity Rover project.The Palmer Glacier on Oregon’s Mount Hood isn’t the moon, but it’s a good place to practice.Some 6,000 feet up the snow-capped mountain, located about 70 miles east of Portland, a multidisciplinary team from the University of Southern California, Texas A&amp;M University, Georgia Institute of Technology, Oregon State University, Temple University, the University of Pennsylvania, and NASA gathered to turn loose a four-legged robot named Spirit into the wild.The team that included engineers, cognitive scientists, geoscientists, and planetary scientists field-tested Spirit as part of the LASSIE Project: Legged Autonomous Surface Science in Analog Environments. Spirit covered a variety of challenging terrains, using his spindly metal legs to amble over, across, and over around shifting dirt, slushy snow, and boulders during five days of testing in summer 2023. Sometimes he expertly traversed the hillside, while at other moments he teetered and fell over — all part of the process to better understand the substrate properties and learn to better walk on these extreme terrains. The practice time Spirit logged produced data that will be used to train future robots for use on intergalactic surfaces, like Earth’s moon and perhaps planets in our solar system.“A legged robot needs to be able to detect what is happening when it interacts with the ground underneath, and rapidly adjust its locomotion strategies accordingly,” says Feifei Qian, an assistant professor of electrical and computer engineering at the USC Viterbi School of Engineering and School of Advanced Computing, which is leading the project funded by NASA. “When the robot leg slips on ice or sinks into soft snow, it inspires us to look for new principles and strategies that can push the boundary of human knowledge and enable new technology. We learn and improve from the observed failures.”Watch this&nbsp;<a href="https://www.youtube.com/watch?v=wBTyelFFE1A" target="_blank">5-minute video</a>&nbsp;produced for the team by documentary filmmaker Sean Grasso.<iframe width="640" height="360" src="https://www.youtube.com/embed/wBTyelFFE1A?&amp;wmode=opaque&amp;rel=0&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> Spirit learns from every step.“Similar to the way that when we walk on uneven surfaces as humans, we can sort of detect how the ground is shifting beneath our feet, a legged robot is capable of the exact same thing,” says Cristina Wilson, a cognitive scientist at Oregon State University.<h2>The more machines the merrier</h2>Qian’s group doesn’t intend to stop at just one robot, wandering the wilderness alone. She and her former colleagues at Penn, Cynthia Sung, Mark Yim, Daniel Koditschek, and Douglas Jerolmack, received a two-year, $2 million grant from NASA they’re calling the TRUSSES Project: Temporarily, Robots Unite to Surmount Sandy Entrapments, Then Separate. They want to help the space agency put teams of robots on the Moon and have them work together on tasks. They would take the knowledge they came in with, and the data they collect on the mission, and communicate those details to each other.“They would sense how the ground conditions are,” Qian says, “and then exchange that information with one another, and collectively form a map of locomotion risk estimation. The team of robots can then use this traversal risk map to inform their planetary explorations: ‘There is an extremely soft sand patch that might be high-risk for wheeled rovers. Come over here, this might be a safer area.’ ”The robots in mind for this kind of work would be more than just Spirit: There would be a wheeled rover (great for payload and long distances), a Hexapedal robot (intermediate payload but better mobility than the wheeled), and dog-like ones like the rugged version of Spirit (highest mobility, shorter distances). And here’s the coolest part of that research, the part that sounds like something the Transformers would do. Or at least a team of castaways on Survivor: If one got in a jam, made immovable by loose dirt or a rock or a ravine, his bot-mates would arrive and link together and form a bridge, or a pyramid, to hoist their pal to safety. And then back to work.“When they plan for the strategy to pull the robot up, they’ll decide what force to exert and what position the robot should go to, while also compiling the terrain information,” Qian says. “That’s the key idea of how to use these capabilities: to both prevent and recover from locomotion failures in extreme terrain.”<h2>Back to Mount Hood</h2>Spirit gets around a variety of natural environments, to learn how to better move on challenging terrains. Qian has let him off his leash on Southern California beaches, and the multi-university team has field-tested him in the soft granules of White Sands National Park in New Mexico. But <a href="https://youtu.be/wBTyelFFE1A" target="_blank">the video</a> shot at Mount Hood shows just how otherworldly that landscape can be in these planetary-analog environments. This provides Spirit with plenty of opportunities to learn on earth, before potentially exploring other planets.“You look around us, it would be very hard to drive up this,” Ryan Ewing, a geologist from NASA Johnson Space Center, <a href="https://youtu.be/wBTyelFFE1A?feature=shared" target="_blank">shares</a>. “But as a legged being, as humans, we can step around it easily. A dog could walk around it easily. So this project is the proving ground that we can enable new science and new mobility on environments that are like other planets.”In fact, a dog is indeed frisking about: Howard, Wilson’s German shepherd, wandered about, with the kind of agility Spirit could only dream of.“We are going to observe how Howard moves in different types of snow and ice conditions,” Qian <a href="https://youtu.be/wBTyelFFE1A?feature=shared" target="_blank">says</a>. “What exactly, out of those combined motions, allows him to succeed on challenging terrain?”The LASSIE Project calls for two more trips for Spirit: to Mount Hood this summer, and to White Sands next year. The TRUSSES team, from USC and Penn, also plans to visit White Sands next year with Spirit and the other, new, multitasking robots. Imagine WALL-E with friends.<hr>The NASA PSTAR (Planetary Science and Technology Through Analog Research) number for this project is 80NSSC22K1313.

Researchers at Georgia Tech have teamed up with NASA and five peer institutions to teach dog-like robots to navigate craters of the moon and other challenging planetary surfaces.

Good Dog: LASSIE Spirit Learns to Walk on the Moon

You’ve all heard of – or, more likely, seen – a precision scan by now.In short, it’s a digital model of what is usually a real-world object, system or process. When done well, for all intents and purposes, the scan is indistinguishable from the real deal. That means it can be used in simulations, for change detection, maintenance – and a whole lot more.There are, of course, existing options out there – and some very good ones.But working with partners, InDro Robotics has created a solution for industries we believe will set a new bar for routine, autonomous 2D and 3D digital captures. It’s a big deal – with significant and positive implications for clients across multiple sectors.“This is an overarching solution with use-cases across a wide variety of verticals,” says InDro Robotics Vice-President Peter King.“We’ve done comprehensive testing of this full-stack solution, and the results have been phenomenal. We are now preparing to roll this out to clients in the industrial sector and beyond.”Below: <a href="https://indrorobotics.ca/precisionscanning/" target="_blank" rel="noopener noreferrer">InDro’s precision scan solution</a>, working a warehouse in California<img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1712764391157-A8A5300-scaled.webp" style="width: 100%px;" class="fr-fic fr-dib" alt="Digital Twin Scanning Robot"><h3 id="isPasted">Comprehensive Digital Twin Solution</h3>InDro’s new industrial scanning solution for digital twin creation brings millimetre-precision to the capturing process.Using a quadruped as a platform, InDro has outfitted the robot with the latest in sensors, including a new Leica LiDAR unit (the system includes three LiDAR units, plus depth cameras and more). The system is capable of true GPS-denied SLAM, exploring a brand new environment while capturing a high-precision 3D or 2D scan.What’s more, with an onboard Machine Vision library, the system is capable of object detection and classification. Use-cases include:<ul><li>Building a precise plan of a manufacturing or warehousing space</li><li>3PL (Third Party Logistics) applications</li><li>Change detection for construction, inventory</li><li>Scans in GPS-denied locations, such as mines or caves (and even some buildings)</li></ul>And that is literally just scratching the surface.“From a manufacturing point of view, for example, if we create a very accurate precision scan, a digital copy of an entire facility can then be used to remanufacture another manufacturing facility,” says King.&nbsp;<h3>Existing Solutions&nbsp;</h3>We’ve all seen digital twins before. Often these are captures of the exteriors or buildings or some other infrastructure (bridges, power lines, pipelines, railroads etc.) where the client is looking for change detection. What is different during this scan vs. the previous one? Is the anomaly going to present an immediate or future problem? Is construction proceeding at the correct pace? Is it time to oder more drywall?Such scans, clearly, can provide very useful data.Though robots (and drones) have been stepping into the interior scanning space, the robotics industry (with few exceptions) is in the early phase of both implementation and adoption. This means many sites still rely on manual scanning: A human being walking around the space with a handheld sensor (usually LiDAR) that creates a point cloud.“Traditionally, this has been done manually,” explains King. “In a lot of cases, it’s required really expensive professionals to travel to come on-site with their own very expensive equipment.”InDro’s precision scan – despite being a complex and comprehensive solution – offers a simpler and more cost-efficient means of capture. Quite simply, our robot is deployed on site to explore the areas the client wants captured. That could be a warehouse floor or an entire, multi-level building. When the robot needs to take a break and re-charge, it returns to its base for a wireless power-up.“It’s traditionally been extremely costly to go and collect this data,” says King. “What we’re offering is a service where we bring the robot, let it work throughout its day, and process the data. Clients will get their scans more affordably, more efficiently – and be in a position to do it more frequently in a cost-effective manner.”<img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1712764457272-A8A5304-scaled.webp" style="width: 100%px;" class="fr-fic fr-dib" alt="Digital Twin Solution"><h3 id="isPasted">Fast, Efficient, Accurate</h3>There’s a wide array of businesses, particularly in supply chain and manufacturing, that frequently update their 2D floor plans. When new tooling or machinery is installed or other physical changes to the location infrastructure take place, companies need to update their digital twin to reflect those alterations. Typically, this is still done manually.“A 2D CAD model is generally done by somebody that’s doing measurements by hand,” says VP King.Wouldn’t it be easier (and less prone to error) to have a fully autonomous robot do the work?“With this precision scan we would let the quadruped run in that new area – wherever things have changed – and automatically update their old file and have a fresh and accurate 2D CAD within a number of hours.”&nbsp;<h3>Tightly Integrated Solution</h3>InDro’s precision scanning solution was built from the ground up to be robust, reliable and – above all – highly accurate. It’s also fast, capable of capturing a 2D scan of even a large facility in less time than a single human shift. (2D scans are often of greater importance, pending the sector, but our solution is equally capable with 3D captures.)“The goal in developing this product has always been about giving clients affordable access to the best and most integrated technology,” says King. “We now have a full-stack solution available for on-demand scans, whether 2D or 3D, indoors or outdoors, and at a price point that makes this a true value proposition for our customers.”Below: Another look at InDro’s new precision scanning solution:<img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1712764517883-A8A5296-scaled.webp" style="width: 100%px;" class="fr-fic fr-dib" alt="Precision Scanning for Digital Twins"><h3 id="isPasted">InDro's Take</h3>We’re obviously proud of this technological accomplishment. We’ve proven this solution both internally and in large warehouse settings in the US – and are gearing up for commercial deployment at scale.“R&amp;D is an exciting but also challenging space,” says InDro Robotics CEO Philip Reece.“We are very selective in the projects we pursue – choosing to innovate and build things only when there’s a clear purpose or a clear client. In this case, it was obvious there was a need for an autonomous, precise solution for companies that require regular or even one-off scans. We are confident in our solution – because we’ve seen the results.”There is, of course, much more behind the technology. But we have to balance how much we reveal with the competitive nature of the market. We can, however, state that this is a proven solution that produces incredible results.Interested in more information? Contact us <a href="https://indrorobotics.ca/connectwithanexpert/" target="_blank">here.</a>

Unveiling a Distinctive Approach for Digital Twin Creation and Industrial Scanning

A New Solution for Autonomous Digital Twins and Industrial Scanning

ANYmal has for some time had no problem coping with the stony terrain of Swiss hiking trails. Now researchers at ETH Zurich have taught this quadrupedal robot some new skills: it is proving rather adept at parkour, a sport based on using athletic manoeuvres to smoothly negotiate obstacles in an urban environment, which has become very popular. ANYmal is also proficient at dealing with the tricky terrain commonly found on building sites or in disaster areas.To teach ANYmal these new skills, two teams, both from the group led by ETH Professor Marco Hutter of the Department of Mechanical and Process Engineering, followed different approaches.<h2>Exhausting the mechanical options</h2>Working in one of the teams is ETH doctoral student Nikita Rudin, who does parkour in his free time. “Before the project started, several of my researcher colleagues thought that legged robots had already reached the limits of their development potential,” he says, “but I had a different opinion. In fact, I was sure that a lot more could be done with the mechanics of legged robots.”With his own parkour experience in mind, Rudin set out to further push the boundaries of what ANYmal could do. And he succeeded, by using machine learning to teach the quadrupedal robot new skills. ANYmal can now scale obstacles and perform dynamic manoeuvres to jump back down from them.<iframe width="640" height="360" src="https://www.youtube.com/embed/REvNnUzVDAA?&amp;wmode=opaque&amp;rel=0&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">&nbsp;</iframe>(Video: ETH Zurich / Nicole Davidson)In the process, ANYmal learned like a child would – through trial and error. Now, when presented with an obstacle, ANYmal uses its camera and artificial neural network to determine what kind of impediment it’s dealing with. It then performs movements that seem likely to succeed based on its previous training.Is that the full extent of what’s technically possible? Rudin suggests that this is largely the case for each individual new skill. But he adds that this still leaves plenty of potential improvements. These include allowing the robot to move beyond solving predefined problems and instead asking it to negotiate difficult terrain like rubble-strewn disaster areas.<h2>Combining new and traditional technologies</h2>Getting ANYmal ready for precisely that kind of application was the goal of the other project, conducted by Rudin’s colleague and fellow ETH doctoral student Fabian Jenelten. But rather than relying on machine learning alone, Jenelten combined it with a tried-and-tested approach used in control engineering known as model-based control. This provides an easier way of teaching the robot accurate manoeuvres, such as how to recognise and get past gaps and recesses in piles of rubble. In turn, machine learning helps the robot master movement patterns that it can then flexibly apply in unexpected situations. “Combining both approaches lets us get the most out of ANYmal,” Jenelten says.As a result, the quadrupedal robot is now better at gaining a sure footing on slippery surfaces or unstable boulders. ANYmal is soon also to be deployed on building sites or anywhere that is too dangerous for people – for instance to inspect a collapsed house in a disaster area.<img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNzExNDk3MTQwNDIwLWltYWdlLmltYWdlZm9ybWF0LjEyODYuMTg0OTg5MDA4Ny5qcGciLCJlZGl0cyI6eyJyZXNpemUiOnsid2lkdGgiOjk1MCwiZml0IjoiY292ZXIifX19" style="width: 100%px;" class="fr-fic fr-dib">ANYmal on a civil defence training ground. (Photograph: ETH Zurich / Fabian Jenelten)<hr><h2 id="isPasted">References</h2>Hoeller D, Rudin N, Sako D, Hutter M: ANYmal Parkour: Learning Agile Navigation for Quadrupedal Robots, Science Robotics, 13 March 2024, doi: <a href="https://doi.org/10.1126/scirobotics.adi7566" target="_blank">external page10.1126/scirobotics.adi7566call_made</a>Jenelten F, He J, Farshidian F, Hutter M: DTC: Deep Tracking Control. Science Robotics 2024, 17: eadh5401, doi: <a href="https://doi.org/10.1126/scirobotics.adh5401" target="_blank">external page10.1126/scirobotics.adh5401call_made</a>

The quadrupedal robot ANYmal practises parkour in a hall at ETH Zurich. (Photograph: ETH Zurich / Nikita Rudin)

The quadrupedal robot ANYmal went back to school and has learned a lot. ETH Zurich researchers used machine learning to teach it new skills: the robot can now climb over obstacles and successfully negotiate pitfalls.

ANYmal can do parkour and walk across rubble

The New B2 and Go2

A Look at the Newest Unitree Quadrupeds