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As robotics rapidly shifts toward systems that can safely assist, collaborate, and adapt in human environments, the ability to perform coordinated, human-like actions has become a defining frontier. From precision assembly to remote intervention, bimanual manipulation and intuitive teleoperation are unlocking new levels of dexterity and autonomy in modern robots.In this webinar, hosted by Franka Robotics, Prof. Fei Chen, one of the leading voices in collaborative and humanoid robotics—shares how the CURI human-like robot is advancing this frontier through innovative control, interaction, and teleoperation strategies. Join us to explore the technologies shaping the next generation of intelligent, versatile robotic systems. <a href="https://wevlv.co/frank_webinar_lp_direct" target="_blank" rel="noopener noreferrer" class="button-main-action">Register now</a><h2>Event Details</h2><h3 id="isPasted">📅 Date: December 10, 2025</h3><table><tbody><tr><td>Location</td><td>Virtual (Join from anywhere)</td></tr><tr><td>Time</td><td>10 AM (CET)</td></tr></tbody></table><h2> </h2><h2 id="isPasted">Who should attend</h2><h2> </h2><ul><li>Industrial automation leaders exploring next-generation collaborative robotic systems</li><li>Robotics engineers and researchers working on manipulation, teleoperation, or human–robot interaction</li><li>Developers and integrators interested in dexterous, human-like robotic capabilities</li><li>Academics and students studying advanced control, bimanual manipulation, or humanoid robotics</li><li>Innovation teams assessing emerging robotic technologies for real-world applications</li></ul><h2>About the Speaker</h2><table><tbody><tr><td><img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNzYzNjM4MzUwODkxLUZlaV9fLnBuZyIsImVkaXRzIjp7InJlc2l6ZSI6eyJ3aWR0aCI6OTUwLCJmaXQiOiJjb3ZlciJ9fX0=" style="width:100%px" class="fr-fic fr-dib" /></td><td>Prof. Fei Chen, Head of the Collaborative and Versatile Robots Laboratory at The Chinese University of Hong Kong, focuses his research on humanoid bimanual manipulation and human-robot collaboration. Prior to joining CUHK, he led research efforts at the Italian Institute of Technology and contributed to numerous European, Italian, and Hong Kong projects. With more than 100 publications, he is also deeply engaged in the IEEE community, serving in key leadership roles across major international robotics conferences and technical committees. In his talk on Bimanual Manipulation and Teleoperation of the CURI Human-like Robot, he highlights how advanced control and interaction strategies are shaping the next generation of intelligent, versatile robotic systems. </td></tr></tbody></table><h2 id="isPasted">Why you should attend</h2><ul><li>Learn how bimanual manipulation enables more complex, human-level tasks in collaborative robotics</li><li>Understand cutting-edge control and interaction strategies used in the CURI human-like robot</li><li>Discover how researchers working on advanced manipulation can benefit from using a highly sensitive <a href="https://franka.de/franka-research-3" target="_blank" id="isPasted">cobot arm</a> that complements bimanual teleoperation studies. <a href="https://wevlv.co/frank_webinar_lp_direct" target="_blank" rel="noopener noreferrer"><img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNzYzNjM4Mjg2MjE2LVdlYmluYXIgcG9zdCAxMCBEZWMgKDEpLmpwZyIsImVkaXRzIjp7InJlc2l6ZSI6eyJ3aWR0aCI6OTUwLCJmaXQiOiJjb3ZlciJ9fX0=" style="width:100%px" class="fr-fic fr-dib" /></a></li></ul>

Join Prof. Fei Chen as he explores advanced bimanual manipulation and teleoperation techniques shaping the future of intelligent human-like robots in this expert-led robotics session.

Bimanual Manipulation and Teleoperation of the CURI Human-like Robot

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Training humanoid robots to hike could accelerate development of embodied AI for tasks like autonomous search and rescue, ecological monitoring in unexplored places and more, say University of Michigan researchers who developed an AI model that equips humanoids to hit the trails. With their new AI framework called <a href="https://lego-h-humanoidrobothiking.github.io/" target="_blank" rel="noreferrer noopener">LEGO-H</a>, the researchers trained simulated, camera-equipped Unitree Robotics humanoids to plan ahead, avoid obstacles, maintain posture and adjust speed and stride to uneven ground. This research was federally funded by the National Science Foundation.“Our model is the first that could give a humanoid robot the ability to see, decide and move entirely on its own—not just walking, but hopping, stepping or jumping as the trail demands. Until now, humanoids have mostly been ‘blind,’ dependent on human operators for every movement decision,” said <a href="https://web.eecs.umich.edu/~stellayu/" target="_blank" rel="noreferrer noopener">Stella Yu</a>, a professor of computer science and engineering and senior author of a study presented at the IEEE Conference on Computer Vision and Pattern Recognition in Nashville in June 2025.<iframe width="640" height="360" src="https://www.youtube.com/embed/-KUSNeXvj2g?&amp;wmode=opaque&amp;rel=0&amp;enablejsapi=1&amp;origin=https://www.wevolver.com" frameborder="0"></iframe>Credit: Lin and Yu, 2025.Traditionally, robots have learned to navigate on flat, unobstructed surfaces using pre-built maps and constant human guidance, with high-level planning (“where to go”) and low-level execution (“how to move”) treated as separate problems. “Unifying navigation and locomotion in a single policy learning framework lets the robots develop their own movement strategies based on the situation without any human pre-programming patterns,” said <a href="https://kwanyeelin.github.io/" target="_blank" rel="noreferrer noopener">Kwan-Yee Lin</a>, a research fellow in computer science and engineering and lead author of the study.In the simulation, humanoid robots are dropped in an unfamiliar trail and asked to navigate to a specific point. They are equipped with visual input, body awareness and a simple GPS direction—such as “the destination is 0.3 miles northeast”—rather than turn-by-turn directions. The virtual 6-foot adult-sized and roughly 4-foot kid-sized robots hiked trails of five different types, each with five difficulty levels. Performance was measured on completeness, safeness and efficiency.<img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1758120425076-Hiking-robots+%281%29.jpg" style="width:100%px" class="fr-fic fr-dib" />A new AI framework called LEGO-H trains humanoid robots to hike complex trails, combining visual perception, decision making and motor execution. The robot uses vision to autonomously anticipate short-term goals and guide locomotion along the trail. The bubble size from large to small indicates the anticipated direction while the color shows the order: orange, then green then gray. Credit: Lin and Yu, 2025.When compared to robots given perfect navigation and environmental information in advance, the simulated autonomous robots’ performance was comparable or better in efficiency and safety. Their built-in body awareness helped prevent damage, and removing that aspect noticeably reduced hiking success, the researchers said.Virtual autonomous robots learned to adapt their body position and motion style based on the terrain. For example, when coming to a tight space, the robots learned to lean sideways to squeeze through. They were also able to decide paths based on obstacles—walking around tall obstacles and stepping over lower obstacles, going around if they were unable to step over.“Amazingly, the virtual robots could regain their balance after a stumble—something not seen in previous humanoids. We didn’t program this. It emerged naturally as the robots learned to interact with their environment,” said Lin.For this first study, the robot’s upper body was kept fixed because adding upper body movements dramatically increases modeling complexity. Now that this proof-of-concept study worked for leg movement, the research team is working towards full-body coordinated hiking to utilize the robot’s full degrees of freedom to maximize stability, safety and efficiency in locomotion.The research team is actively working on adapting these policies to physical humanoids in the real world.

Now able to learn locomotion and navigation together, robots develop balanced gaits and safe routes.

Simulated humanoid robots learn to hike rugged terrain autonomously

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There’s been a lot of buzz over bipedal robots in recent years.Companies like Boston Dynamics, Agility Robotics, Unitree and others have developed powerful algorithms and leading edge hardware to make what was once science fiction a reality. There are now an increasing number of walking (and sometimes talking) upright robots that get around on two legs. These tend to be humanoids, but they are bipedal.There’s a certain cool factor to seeing robots that walk like people. But the push for bipedal robots is also driven by infrastructure: Factories and other settings where such devices might be deployed have been built for people. So robots that can walk and are roughly human size can work in such spaces without infrastructure changes.“With the automobile, we had to build roads,” said Jonathan Hurst, Chief Technology Officer of Agility Robotics, in an explanatory video. “With legged robots we’ve already built the infrastructure. Legged robots are going to change the world as much as the automobile did.”As the saying goes, time will tell. But before we proceed, it’s worth mentioning that bipedal doesn’t necessarily mean humanoid.“A humanoid typically mimics the human form – so it has a head, torso, arms and legs,” explains Luke Corbeth, InDro’s Head of R&amp;D Sales.“Bipedal simply means it walks on two legs, but it doesn’t need to look human. So while most humanoids are bipedal, not all bipedal robots are humanoids.”Below: Agility’s Cassie – a bipedal, non-humanoid robot. Immense R&amp;D went into developing this machine, with many of the lessons learned applied to its current Digit humanoid<iframe width="640" height="360" src="https://www.youtube.com/embed/DdojWYOK0Nc??si=WL0wpUwIkrD8hMN2&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;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;</iframe><h3 id="isPasted">The Bipedal-Humanoid Connection</h3>As the video illustrated, bipedal robots aren’t necessarily humanoid (though they can be). But since the non-humanoid versions don’t have arms or manipulators, what are the use-cases?First off, they’re critical tools in the R&amp;D space. Before any company attempts a full-blown humanoid, it needs to perfect locomotion, balance and gait. That, of course, requires intensive hardware and software development. Many in the research space don’t have the time or resources to build from scratch. By starting with an existing bipedal robot they can rapidly start working on improving algorithms, adding autonomy stacks, machine vision, etc.“Achieving stable and efficient bipedal locomotion is really the first critical milestone – so it involves doing things like balancing the gait, being very energy efficient and knowing how to recover from various disturbances,” says Corbeth. “But once that’s dialed in, you can build advanced capabilities on top of it, things like manipulation or autonomous navigation. So starting with a bipedal platform can help clients achieve their ultimate goals much sooner”Not surprisingly, clients for bipedal, non-humanoid platforms are often in the R&amp;D space.“For anyone specifically researching bipedal locomotion, these devices make sense,” he adds. “It allows them to really focus on research and control, computer vision and AI applications. It’s an accessible platform for labs to really accelerate their work on humanoids.”In other words, perfecting a bipedal platform is critical in the development of full humanoid robots.&nbsp;<h3>Rise of the Humanoids</h3>We recently took a dive into humanoids <a href="https://indrorobotics.ca/the-rise-of-the-humanoid-robots/" target="_blank">here</a>.To recap briefly, humanoids are on the rise because their form factor allows them to integrate with existing infrastructure. With arms and manipulators/end effectors, they can carry out many of the tasks that humans perform. Bipedal design means they can climb stairs or navigate other obstacles. Even humanoids with wheels or tracks can now carry out these manoeuvres.“Humanoid robots have become one of the most frontier topics in the field of robot research [<a href="https://ietresearch.onlinelibrary.wiley.com/doi/10.1049/cim2.12080#cim212080-bib-0001" data-tab="pane-pcw-references" target="_blank">1</a>],” states <a href="https://ietresearch.onlinelibrary.wiley.com/doi/10.1049/cim2.12080" target="_blank">this research paper</a>. “Owing to the human-like structures and strong environmental adaptability [<a href="https://ietresearch.onlinelibrary.wiley.com/doi/10.1049/cim2.12080#cim212080-bib-0002" data-tab="pane-pcw-references" target="_blank">2</a>], biped robots can directly operate the tools and vehicles used by humans, showing wide application prospects in fields such as home service, industrial manufacturing and environmental detection [<a href="https://ietresearch.onlinelibrary.wiley.com/doi/10.1049/cim2.12080#cim212080-bib-0003" data-tab="pane-pcw-references" target="_blank">3</a>]…Ongoing research…shows great potential in human–robot collaboration and autonomous operation [<a href="https://ietresearch.onlinelibrary.wiley.com/doi/10.1049/cim2.12080#cim212080-bib-0006" data-tab="pane-pcw-references" target="_blank">6</a>].”Many of the tasks bipedal robots will eventually carry out aren’t even fully known yet, as these new commercial products are very much – despite some really impressive machines – in the early stages of adoption and deployment. It’s a safe bet that every company currently selling bipedal or humanoid robots is hard at work in the lab on the next generation. There’s a lot of development in the pipeline.“Better battery life is kind of on everyone’s wishlist – the runtime of a humanoid or bipedal robot simply isn’t as long as some of the traditional wheeled or track systems. There are also other things like faster and safer locomotion and, of course, dexterous hands,” says Corbeth.We hit up AI for some thoughts on where these machines are going. It concurs that the full benefits of bipedal robots have yet to be realised.“While bipedal robots offer unique advantages, it’s worth noting that they are still under development, and their efficiency and practicality in certain applications are still being evaluated.&nbsp;For example, wheeled robots might be more energy-efficient for certain tasks on flat surfaces.&nbsp;However, for navigating complex, unstructured environments and interacting with human-scale tools and spaces, bipedal robots offer a promising solution.”In addition to humanoids, InDro now offers a strictly bipedal, non-humanoid platform primarily for R&amp;D. As with most platforms, our engineers are currently working on expanding its capabilities to enable it more fully for R&amp;D and industrial clients. We will soon be integrating <a href="https://indrorobotics.ca/the-new-indro-command-module-amazing-power-in-a-tiny-package/" target="_blank">InDro Cortex</a>, a brain-box that enables everything from remote teleoperation and sensor integration to fully autonomous and/or easily programmable missions.“We’re looking to add our Cortex solution – the hardware and the software and the autonomy – to our humanoids and bipedal robots,” says Corbeth. “We see opportunities to integrate advanced autonomy, teleoperation and perception pipelines into this equipment…making them a turnkey solution for advanced humanoid development and real-world testing.”Below: A great video explanation of the bipedal advantage, followed by the bipedal robot InDro now has available<iframe width="640" height="360" src="https://www.youtube.com/embed/mHmmySGdaoM??si=_YUtIonJpOBhBYy3&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;&nbsp;</iframe><img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1752856176771-Biped+6.jpg" style="width: 100%px;" class="fr-fic fr-dib" alt="Biped Robot"><h3 id="isPasted">InDro's Take</h3>Bipedal robots are the precursor to full-blown humanoids. Not only does the humanoid form factor work well in existing infrastructure, they’re seen by many as the ideal collaborative robots, or co-bots. People seem more at ease with something that looks vaguely human (with the notable exception of Terminator’s T800).“The human form factor is just intuitive for people to interact with – and the similar size helps them use human tools and really fit in well in workspaces,” says Corbeth. “Some may argue as well they also kind of build trust, which is crucial for collaborative robots operating around or with people.”And for those in the R&amp;D space looking for a bipedal-only platform, we’ve got you covered.We look forward to sharing more about our bipedal and humanoid robots in future, particularly once we’ve supercharged them with InDro Cortex. If you’re curious to learn more, <a href="https://indrorobotics.ca/thebiped/" target="_blank" rel="noopener noreferrer">checkout the biped platform here</a>.

Exploring the Impact of Advanced Bipedal Robotics

Bipedal Robots Step Into The Scene

<h1 id="isPasted">Unitree G1 mass production version, leap into the future!</h1>Over the past few months, Unitree G1 robot has been upgraded into a mass production version, with stronger performance, ultimate appearance, and being more in line with mass production requirements. We hope you like it.

Over the past few months, Unitree G1 robot has been upgraded into a mass production version, with stronger performance, ultimate appearance, and being more in line with mass production requirements. We hope you like it.

Unitree G1 mass production version, leap into the future!

In order to advance the convenience of data collection for humanoid robots, we refer to other solutions to do the adaptation development and open source.Github：<a tabindex="0" href="https://www.youtube.com/redirect?event=video_description&redir_token=QUFFLUhqbGEtVm9yOHhmdlZEVFpnUTNSUEdLdzJCZG9XUXxBQ3Jtc0tsTmEweUk5aWQ4LWFvVTRQcGdUb182R2F2dFM3cENCb1lUREJSbnhwTlgwN2ptR1pSRlAwakxBM284QWZYc01JTWhYektEYUZ3ZGhXenlEbVAwWkgtXzN6c1QybV9xNkNlS2tfS3JqbzhjYWJ2UGtDVQ&q=https%3A%2F%2Fgithub.com%2Funitreerobotics%2Favp_teleoperate&v=pNjr2f_XHoo" rel="nofollow" target="_blank" data-immersive-translate-walked="d184844b-18ce-4d8f-9392-ad8f851f3836">https://github.com/unitreerobotics/av...</a>Kinect：<a tabindex="0" href="https://www.youtube.com/redirect?event=video_description&redir_token=QUFFLUhqa25pczNWM3NDT2RoaXpVb3o3MWFfVTBtS2lnUXxBQ3Jtc0trN0JLVlg5ZVRxZXdpcUhPXzFkTzZXNlp4SEtkTms2aTRCZUZhc2o5cGVONzFNdHVRemd5SUFDSVhWUlgwbzlXaTlwVDF3c1p0SE5nQXBnYy1hd3NuamxlYzM1TW1NSGdVMThjXzIxZlRKeEF3cXJUNA&q=https%3A%2F%2Fgithub.com%2Funitreerobotics%2Fkinect_teleoperate&v=pNjr2f_XHoo" rel="nofollow" target="_blank" data-immersive-translate-walked="d184844b-18ce-4d8f-9392-ad8f851f3836">https://github.com/unitreerobotics/ki...</a> Official Website: www.unitree.com&nbsp;Twitter: twitter.com/UnitreeRobotics&nbsp;LinkedIn: www.linkedin.com/company/unitreerobotics

In order to advance the convenience of data collection for humanoid robots, we refer to other solutions to do the adaptation development and open source.

Open Source Unitree First View Teleoperation for Humanoid Robots

<h1 data-immersive-translate-walked="96540da1-b11f-43db-91ca-401597307f25" id="isPasted">Unitree Go2 New Upgrade</h1>The evolution of intelligent robots is full of surprises and exciting moments every day. Let's have fun together. 🥳🥳🥳Official Website: www.unitree.com&nbsp;Twitter: twitter.com/UnitreeRobotics&nbsp;Youtube: @unitreerobotics &nbsp;&nbsp;&nbsp;LinkedIn: www.linkedin.com/company/unitreerobotics

The evolution of intelligent robots is full of surprises and exciting moments every day.
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<h1 id="isPasted">Unitree Combat Competition Highlights May 25, 2025</h1>A historic moment in human history: The first-ever humanoid robot combat competition(Livestream)

A historic moment in human history: The first-ever humanoid robot combat competition(Livestream)

Unitree Combat Competition Highlights May 25, 2025

This is Part 3 of a four-part series. See Part 1: <a href="https://www.wevolver.com/article/mastering-multitasking-exploring-the-distributed-processing-capabilities-of-tdks-advanced-robotics" target="_blank" rel="noopener noreferrer">Mastering Multitasking: Exploring the Distributed Processing Capabilities of TDKs Advanced Robotics</a> and Part 2: <a href="https://www.wevolver.com/article/sensing-the-world-how-tdks-multi-sensor-fusion-improves-perception-in-industrial-and-service-robots" target="_blank" rel="noopener noreferrer">Sensing the World: How TDK’s Multi-Sensor Fusion Improves Perception in Industrial and Service Robots. </a><h2>Introduction</h2>Humanoid robotics have seen remarkable growth in recent years, with applications expanding across healthcare, home assistance, and industrial sectors. The global market for humanoid robots is expected to grow from USD $2.03 billion in 2024 to USD 13.25 billion by 2030.[1] However, this growth has been accompanied by significant challenges, notably in motion control and stability. The key to addressing these issues is the Inertial Measurement Unit (IMU), an important component for replicating human-like movements in humanoid robots. IMUs track orientation, acceleration, and movement, so that humanoid robots can replicate human-like movements effectively.  TDK Corporation, a leader in electronic components and systems, has developed a unique MEMS-based 6-axis IMU technology that is transforming motion control in humanoid robotics. This advanced IMU integrates accelerometer and gyroscope data to provide real-time motion tracking, which enables precise limb control, dynamic stability, and fall detection in humanoid robots.[2]By combining high-precision sensors with sophisticated algorithms, TDK’s 6-axis IMU sets a new standard for motion control in the field of service robotics.<h2>The Need for Precision in Humanoid Robots</h2>Humanoid robots face unique motion challenges that require exacting solutions:<ul><li>Balance and Stability — Robots working in unpredictable environments near humans must stay upright on uneven terrain.</li><li>Real-Time Motion Tracking — Robots need instant data processing and coordination to move naturally and respond to external stimuli.</li><li>Fall Detection and Recovery — Preventing and recovering from falls is critical for safe operation, especially in spaces designed for humans.</li></ul>Traditional motion sensors often struggle to keep up, and basic IMUs often fail to compensate for sudden disturbances. This leads to small errors that add up over time. Additionally, although optical and LiDAR-based systems are extremely accurate, they are computationally demanding and can introduce delays, which makes them less ideal for fast, responsive movement.[3]The limitations of conventional sensors show that there is a need for more advanced solutions in humanoid robotics. TDK’s 6-axis IMU addresses these shortcomings by providing high-precision, low-latency motion data. This responsive IMU helps humanoid robots move with greater agility and stability, bringing them a step closer to human-like motion. <h2>How TDK’s 6-Axis IMU Solves These Challenges</h2><h3>Advanced Motion Tracking Through Sensor Fusion</h3>TDK’s 6-axis IMU combines accelerometers and gyroscopes to gather precise motion data. The working mechanism involves these components:<ul><li>Accelerometers measure linear acceleration in three axes.</li><li>Gyroscopes detect angular velocity around three axes.</li><li>Sensor fusion algorithms integrate both of these data streams to predict movement with accuracy.</li></ul>Quantified performance indicators for TDK’s ICM-42688-P IMU:<ul><li>TDK’s ICM-42688-P IMU achieves a 40% lower noise figure compared to traditional consumer-grade IMUs.</li><li>Temperature stability is improved by 2x, keeping data accurate across environmental conditions.</li><li>The device features a high-resolution analog-to-digital converter that provides an 8x increase in gyroscope resolution and a 4x increase in accelerometer resolution.</li><li>Rapid data processing and a 100% accurate clock eliminate timing errors for near-instantaneous motion tracking.[4]</li></ul>This fusion technology has several benefits:<ul><li>Drift Compensation — Advanced algorithms correct sensor drift, which keeps data accurate long term.</li><li>Kalman Filtering — This technique refines and enhances motion estimates by combining sensor data with predictive models.</li><li>Ultra-Low Latency — The rapid data processing results in near-instantaneous motion tracking.[5]</li><li>AI-Powered Motion Predictions — IMU data can be used for AI/ML predictive models for more human-like movement.  </li></ul><h3>Enhancing Dynamic Stability in Humanoid Robots</h3>Dynamic stability is critical for humanoid robots, and TDK’s ICM-42688-P IMU helps maintain this with:<ul><li>Real-Time Posture Correction — The IMU detects imbalances and triggers adjustments to the robot’s stance. It reaches a heading accuracy of ≤10° per hour and operates at a data rate of up to 1000 Hz, enabling fast detection and correction of imbalances. </li><li>Adaptive Gait Optimization — The IMU’s high-frequency (up to 1000 Hz) keeps the robot walking smoothly on uneven terrain by continuous adjustment of leg movements.</li><li>Multi-Sensor Integration — IMU data is fused with force sensor feedback and geometric models using Extended Kalman Filters (EKF). This fusion reduces contact force estimation errors to within 5 N·m and maintains balance stability above 95% in dynamic environments. When IMU and force sensor data are combined, interference errors are reduced by about 20%, and overall pose estimation accuracy improves by up to 30%</li></ul><h3>Fall Detection and Recovery</h3>Safety is a priority in robotics, especially in assistive applications. The 6-axis IMU helps prevent falls by:<ul><li>Detecting sudden acceleration changes that might signal a potential fall.</li><li>Analyzing body tilt and weight shifts to predict instability.</li><li>Triggering corrective actions before impact, reducing the risk of falls.</li></ul>These capabilities make TDK’s IMU valuable in applications like assistive robotics, where fall prevention is required for user safety.[6]<h2>Real-World Applications of TDK’s 6-Axis IMU</h2><h3>Assistive Robotics in Healthcare</h3>TDK’s IMU technology finds significant applications in healthcare robotics:<ul><li>Exoskeletons for Rehabilitation — Helps impaired patients regain movement with precise motion control and balance support.</li><li>Elderly Support Robots — Improves stability for home care robotic assistants by providing safe navigation and facilitating interaction in domestic environments. [7]</li></ul><h3>Home Service Robots</h3>The 6-axis IMU also has applications in domestic settings, where there are opportunities to improve robotic efficiency:<ul><li>Autonomous Navigation — Enables smooth movement for cleaning, delivery, and household assistance.</li><li>Precision in Object Handling — Provides stability and control for AI-powered robotic arms, which allows for safe handling of household items.</li></ul><h3>Industrial and Inspection Robotics: ANYbotics Case Study</h3>TDK Ventures has partnered with ANYbotics, a leader in autonomous industrial inspection robots. Their ANYmal robot integrates TDK’s IMU technology to enhance performance in:<ul><li>Harsh Environments — Enables stable movement on uneven surfaces and improves obstacle avoidance in industrial settings. The IMU ensures that the robot maintains balance even in hazardous areas such as offshore platforms, underground tunnels, and power plants.</li><li>Factory Automation — Supports self-balancing robotic arms for precise manufacturing tasks, increasing efficiency in automated production lines. The IMU's real-time motion tracking allows robots to detect micro-vibrations and adjust accordingly, reducing errors in delicate assembly processes.[8]</li></ul>ANYmal’s ability to navigate complex environments with high stability demonstrates how TDK’s IMU complements robotic autonomy. By improving movement precision and safety, this technology provides industries with a way to reduce human risk exposure while maintaining high operational efficiency.<h2>TDK’s Competitive Edge in IMU Technology</h2><h3>TDK's 6-axis IMU has several advantages that make it stand out from conventional IMUs:</h3><ul><li>High Precision — Delivers more accurate motion data with minimal drift.</li><li>Robust Noise Filtering — Maintains clean data even in noisy environments.</li><li>Compact Design — MEMS-based miniaturization helps keep robot designs lightweight and power-efficient.[9]</li></ul>TDK’s MEMS-based IMU is unique because it can provide micro-scale motion tracking with high precision, which is key to replicating human-like movements in robots. The compact size of the technology also makes way for the development of more agile and energy-efficient robotic systems.Looking ahead, TDK is exploring AI and machine learning integration:<ul><li>AI-powered motion predictions can refine IMU tracking for even greater accuracy.</li><li>Adaptive learning algorithms could enable humanoid robots to improve movement by learning about the environment over time.</li></ul><h2>Conclusion</h2>TDK’s 6-axis IMU is positioned to shape the future of humanoid robotics with industry-leading precision, robust noise filtering, and ultra-compact MEMS design. Devices like the ICM-42688-P offer precise, real-time motion data and unparalleled performance metrics that enable more stable, agile, and safe robotic systems. These advancements position TDK at the forefront of robotic motion tracking for replicating human-like movement.As TDK continues to innovate in MEMS-based IMU technology, we can anticipate even more advanced and capable robotic systems in years to come. Learn more about TDK’s innovative advancements at <a href="https://www.tdk.com/en/index.html">https://www.tdk.com/en/index.html</a>.<hr /><h3>Reference</h3>[1] Markets and Markets. “Humanoid Robot Market Size, Share &amp; Growth”. Accessed from <a href="https://www.marketsandmarkets.com/Market-Reports/humanoid-robot-market-99567653.html" id="isPasted">https://www.marketsandmarkets.com/Market-Reports/humanoid-robot-market-99567653.html</a>[2] TDK IMU Product Page. Accessed from <a href="https://product.tdk.com/en/products/sensor/mortion-inertial/imu/index.html" id="isPasted">https://product.tdk.com/en/products/sensor/mortion-inertial/imu/index.html</a> [3] Ohidul Islam. “Challenges in Humanoid Robotics and How to Overcome Them”. Accessed from <a href="https://robozaps.com/challenges-in-humanoid-robotics/" id="isPasted">https://robozaps.com/challenges-in-humanoid-robotics/</a> [4] Shannon Davis. “TDK Launches High-Performance 6-axis IMU with Industry-Leading Motion Sensor Performance”. Semiconductor Digest. Accessed from <a href="https://www.semiconductor-digest.com/tdk-launches-high-performance-6-axis-imu-with-industry-leading-motion-sensor-performance/" id="isPasted">https://www.semiconductor-digest.com/tdk-launches-high-performance-6-axis-imu-with-industry-leading-motion-sensor-performance/</a> [5] TDK IMU Product Page.[6] “TDK launches high-performance 6-axis IMU with industry-leading motion sensor performance for IoT, robotics, AR/VR and wearable applications”. Industry EMA. Accessed from <a href="https://www.industryemea.com/news/27191-tdk-launches-high-performance-6-axis-imu-with-industry-leading-motion-sensor-performance-for-iot,-robotics,-ar-vr-and-wearable-applications" id="isPasted">https://www.industryemea.com/news/27191-tdk-launches-high-performance-6-axis-imu-with-industry-leading-motion-sensor-performance-for-iot,-robotics,-ar-vr-and-wearable-applications</a> [7] Rika Melissa. “Service Robot Market: Trends, Growth, and Future Outlook” (22 May 2024). Sateton. Accessd from <a href="https://statzon.com/insights/humanoid-helpers-and-beyond-service-robot-market-expansion" id="isPasted">https://statzon.com/insights/humanoid-helpers-and-beyond-service-robot-market-expansion</a>[8] “TDK Ventures Invests in ANYbotics, a World Leader in Industrial Inspection Autonomous Robots” (11 Dec. 2024). Accessed from <a href="https://tdk-ventures.com/news/announcements/tdk-ventures-invests-in-anybotics-a-world-leader-in-industrial-inspection-autonomous-robots/" id="isPasted">https://tdk-ventures.com/news/announcements/tdk-ventures-invests-in-anybotics-a-world-leader-in-industrial-inspection-autonomous-robots/</a>[9] TDK IMU Product Page.

Photo by Possessed Photography on Unsplash

By combining high-precision sensors with sophisticated algorithms, TDK's 6-axis IMU sets a new standard for motion control in the field of service robotics.

Innovation in Motion: How TDK's 6-Axis IMU Enables Precise Movement in Humanoid Robots

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

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