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This robotic hand can weave itself together in minutes. Allonic developed a process that "braids" robot bodies around a 3D-printed skeleton in a single automated step. The tech draws from the textile industry, using braided fibers instead of traditional mechanical joints and bearings. Their braiding system grows tendon-driven structures... directly onto skeletal cores, creating flexible yet durable parts without screws or assembly. One finger only needs 4 skeletal elements. Then thousands of braided fibers wrap around them to handle force and articulation. The software converts designs directly into machine code that runs the braiding process. But what matters is that robotic hands like this can cost up to $30,000, ~20-30% of a humanoid robot's total price. Allonic's braiding process could crush those costs while enabling custom designs at scale.show more

Rowan Cheung

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75,066 次观看 • 6 个月前 •via X (Twitter)

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THE WOVEN ROBOT! Wow! The woven robot hand is here and it is absolutely game-changing. Allonic just braided thousands of tendon-like fibers around a 3D-printed skeleton in minutes. No joints. No screws. No human assembly. Pure biomimetic tissue that flexes, grips, and lasts like biology itself. This isn’t incremental. This is the breakthrough that collapses robot hand costs from $30,000 to pennies. The old world of expensive, fragile robotic limbs is over. Now humanoid robots can build more of themselves scalable, replicable, anywhere. Robots building Robots building Robots, yeah you get it. In your freaking garage! Massive opportunities are about to explode as work as we know it fades. Rent one, have it build your fleet, send it back, repeat. Thousands if you want. The age of woven machines begins.

THE WOVEN ROBOT! Wow! The woven robot hand is here and it is absolutely game-changing. Allonic just braided thousands of tendon-like fibers around a 3D-printed skeleton in minutes. No joints. No screws. No human assembly. Pure biomimetic tissue that flexes, grips, and lasts like biology itself. This isn’t incremental. This is the breakthrough that collapses robot hand costs from $30,000 to pennies. The old world of expensive, fragile robotic limbs is over. Now humanoid robots can build more of themselves scalable, replicable, anywhere. Robots building Robots building Robots, yeah you get it. In your freaking garage! Massive opportunities are about to explode as work as we know it fades. Rent one, have it build your fleet, send it back, repeat. Thousands if you want. The age of woven machines begins.

Brian Roemmele

21,747 次观看 • 6 个月前

Just saw something that actually feels like a real leap in robotics hardware.👋 Allonic built a robot hand using 3D Tissue Braiding,basically weaving high-strength fibers around a minimal rigid skeleton the way human connective tissue wraps around bone. No hundreds of screws, bearings, cables or fiddly joints. Instead,a continuous automated process that creates the tendons, soft tissue & compliant structure all at once. The outcome is wild: »strong yet naturally soft & safe for close human interaction »surprisingly dexterous »produced from digital design→physical part in minutes »cost drops so much that you could eventually swap end-effectors like disposable gloves This is starting to feel like the moment robotic bodies get their own “3D printing revolution”. Hardware iteration speed finally approaching software speed. If this scales, it could be one of the missing pieces that lets dexterous humanoid robots move from lab → factories → homes. (Oh, and the company just raised $7.2M Pre-Seed,largest ever in Hungary. Budapest-based with US HQ. Led by Visionaries Club + angels from OpenAI, Hugging Face, ETH Zurich, Northwestern etc.) Prototype hand looks insane,the woven fiber texture is unreal.

Just saw something that actually feels like a real leap in robotics hardware.👋 Allonic built a robot hand using 3D Tissue Braiding,basically weaving high-strength fibers around a minimal rigid skeleton the way human connective tissue wraps around bone. No hundreds of screws, bearings, cables or fiddly joints. Instead,a continuous automated process that creates the tendons, soft tissue & compliant structure all at once. The outcome is wild: »strong yet naturally soft & safe for close human interaction »surprisingly dexterous »produced from digital design→physical part in minutes »cost drops so much that you could eventually swap end-effectors like disposable gloves This is starting to feel like the moment robotic bodies get their own “3D printing revolution”. Hardware iteration speed finally approaching software speed. If this scales, it could be one of the missing pieces that lets dexterous humanoid robots move from lab → factories → homes. (Oh, and the company just raised $7.2M Pre-Seed,largest ever in Hungary. Budapest-based with US HQ. Led by Visionaries Club + angels from OpenAI, Hugging Face, ETH Zurich, Northwestern etc.) Prototype hand looks insane,the woven fiber texture is unreal.

CyberRobo

263,097 次观看 • 7 个月前

New Episode: Benedek Tasi is leading Allonic, a Hungarian robotics startup leveraging textile technology to create humanoid hands that mimic human anatomy. We discuss their 3D braiding process, engineering complexities, and Benedek’s vision for the future of robotics. 0:52 Intro 1:32 Prior work in bio-inspired solutions 4:05 Drawing inspiration from textile industries 6:01 Innovations in braiding manufacturing 7:46 Speed of production 9:03 Physics of load distribution in fibers 9:45 Inherent limitations of tendon-driven systems 12:51 Solving precision and dexterity challenges 14:58 Full musculoskeletal humanoid robots? 17:14 Growth plans and technological expansion 18:38 Long-term vision for robotic infrastructure

New Episode: Benedek Tasi is leading Allonic, a Hungarian robotics startup leveraging textile technology to create humanoid hands that mimic human anatomy. We discuss their 3D braiding process, engineering complexities, and Benedek’s vision for the future of robotics. 0:52 Intro 1:32 Prior work in bio-inspired solutions 4:05 Drawing inspiration from textile industries 6:01 Innovations in braiding manufacturing 7:46 Speed of production 9:03 Physics of load distribution in fibers 9:45 Inherent limitations of tendon-driven systems 12:51 Solving precision and dexterity challenges 14:58 Full musculoskeletal humanoid robots? 17:14 Growth plans and technological expansion 18:38 Long-term vision for robotic infrastructure

The Humanoid Hub

40,081 次观看 • 7 个月前

It's a 3D printer, and 3D assembly station! 🖨️ The Functgraph developed at Meiji University starts as a regular 3D printer but upgrades itself into a mini factory. It can print parts for its own tools, pick them up, clean them, and put them together, all by itself. Think of it like a robot that can 3D print a spatula, assemble it, and then use it to flip pancakes. 🥞 Instead of just printing objects, the Functgraph can actually perform physical tasks, like folding laundry or slicing vegetables, by using printed and assembled tools. It’s a step toward the idea of a robot that can download "apps" as physical skills, much like your phone downloads software! 👀

It's a 3D printer, and 3D assembly station! 🖨️ The Functgraph developed at Meiji University starts as a regular 3D printer but upgrades itself into a mini factory. It can print parts for its own tools, pick them up, clean them, and put them together, all by itself. Think of it like a robot that can 3D print a spatula, assemble it, and then use it to flip pancakes. 🥞 Instead of just printing objects, the Functgraph can actually perform physical tasks, like folding laundry or slicing vegetables, by using printed and assembled tools. It’s a step toward the idea of a robot that can download "apps" as physical skills, much like your phone downloads software! 👀

Lukas Ziegler

149,956 次观看 • 1 年前

A lot of robot learning pipelines treat embodiment mismatch as a software problem. Collect data with one device, retarget the motion to another robot, and try to deal with the differences later. TwinDEX flips that idea around. This system is from a Chinese robotics company called X Square. Instead of starting with a generic data-collection device, the team co-designs a wearable three-finger end-effector and a robotic hand as two sides of the same learning system. They align the things that actually matter during manipulation: joint structure, link proportions, contact geometry, surface properties, visual appearance, sensing, and timing. That matters because dexterous manipulation is much more than matching hand poses. A few millimeters of contact error or a different force relationship can completely change how a task is executed. In the collection evaluation, TwinDEX delivered up to 5.3 times the effective throughput of on-robot teleoperation. It’s a useful reminder that scaling robot learning may not only be about bigger models and more data. Sometimes the hardware collecting the data is part of the data problem itself.

A lot of robot learning pipelines treat embodiment mismatch as a software problem. Collect data with one device, retarget the motion to another robot, and try to deal with the differences later. TwinDEX flips that idea around. This system is from a Chinese robotics company called X Square. Instead of starting with a generic data-collection device, the team co-designs a wearable three-finger end-effector and a robotic hand as two sides of the same learning system. They align the things that actually matter during manipulation: joint structure, link proportions, contact geometry, surface properties, visual appearance, sensing, and timing. That matters because dexterous manipulation is much more than matching hand poses. A few millimeters of contact error or a different force relationship can completely change how a task is executed. In the collection evaluation, TwinDEX delivered up to 5.3 times the effective throughput of on-robot teleoperation. It’s a useful reminder that scaling robot learning may not only be about bigger models and more data. Sometimes the hardware collecting the data is part of the data problem itself.

Alamin

48,112 次观看 • 1 个月前

AI in CAD just went from “make me a part” to “build me the damn machine.” Using Autodesk Fusion MCP, the agent is working inside a real mechanical assembly with a chassis, shafts, gears, bearings, brackets, repeated hardware, and multiple components that all have to stay aligned with each other. That is a completely different problem from generating one clean 3D object. You can inspect the assembly from different angles, isolate sections, dig into individual joints, and keep working on the same engineering project instead of starting from another prompt-generated blob. The important part is not that AI can create geometry anymore. It is that it can operate inside the structure of a real CAD project where every component depends on what is around it. Once this gets reliable, a lot of mechanical CAD starts looking suspiciously simple: describe the system, inspect what the agent built, then tell it what to change.

AI in CAD just went from “make me a part” to “build me the damn machine.” Using Autodesk Fusion MCP, the agent is working inside a real mechanical assembly with a chassis, shafts, gears, bearings, brackets, repeated hardware, and multiple components that all have to stay aligned with each other. That is a completely different problem from generating one clean 3D object. You can inspect the assembly from different angles, isolate sections, dig into individual joints, and keep working on the same engineering project instead of starting from another prompt-generated blob. The important part is not that AI can create geometry anymore. It is that it can operate inside the structure of a real CAD project where every component depends on what is around it. Once this gets reliable, a lot of mechanical CAD starts looking suspiciously simple: describe the system, inspect what the agent built, then tell it what to change.

Rina

14,154 次观看 • 1 个月前

Humanoid robots are starting to build humanoid robots. UBTECH just put a 14,000㎡ humanoid robot factory into operation in Liuzhou, China, with a designed takt time of one humanoid every 10 minutes and planned annual capacity in the tens of thousands. What’s interesting is that humanoid robots are already part of the production process. Cruzr Y1 and Y2 handle depalletizing, palletizing, material feeding and transport, using 3D vision to adapt to shifted boxes and changing pallet patterns. On the assembly side, Walker S2 and Cruzr are produced on the same line alongside cobots, autonomous logistics vehicles and assistive manipulators. The factory also has a 65㎡ automated warehouse capable of storing 112 humanoids, with AGVs, industrial robots and stacker cranes coordinated as one system. Before production, the factory was modeled 1:1 in Siemens Plant Simulation, covering workstations, racks and AGVs. Each robot gets its own SN, with components, batches, assembly parameters and inspection data tracked all the way to delivery. Humanoid robots are now entering automated manufacturing at the 10,000-unit scale. The next milestone may be when they can take part in enough of the assembly, testing and production process to truly build robots themselves.

Humanoid robots are starting to build humanoid robots. UBTECH just put a 14,000㎡ humanoid robot factory into operation in Liuzhou, China, with a designed takt time of one humanoid every 10 minutes and planned annual capacity in the tens of thousands. What’s interesting is that humanoid robots are already part of the production process. Cruzr Y1 and Y2 handle depalletizing, palletizing, material feeding and transport, using 3D vision to adapt to shifted boxes and changing pallet patterns. On the assembly side, Walker S2 and Cruzr are produced on the same line alongside cobots, autonomous logistics vehicles and assistive manipulators. The factory also has a 65㎡ automated warehouse capable of storing 112 humanoids, with AGVs, industrial robots and stacker cranes coordinated as one system. Before production, the factory was modeled 1:1 in Siemens Plant Simulation, covering workstations, racks and AGVs. Each robot gets its own SN, with components, batches, assembly parameters and inspection data tracked all the way to delivery. Humanoid robots are now entering automated manufacturing at the 10,000-unit scale. The next milestone may be when they can take part in enough of the assembly, testing and production process to truly build robots themselves.

CyberRobo

17,883 次观看 • 20 天前

A robotic ballet! 🩰 Coordinating multiple robot arms on a busy factory floor is notoriously complex. Each arm needs to move without colliding with its neighbors or the surrounding equipment, and today that planning is still mostly done by hand, a process that takes specialists hundreds of hours. Researchers at UCL, Google DeepMind, and Intrinsic have introduced RoboBallet, a new AI system that tackles this challenge head-on. Using a combination of graph neural networks and reinforcement learning, RoboBallet learns how to coordinate many robots in real time, generating smooth, collision-free motion plans in seconds instead of days. In tests, the system handled up to 40 tasks with eight arms working together, far beyond the limits of traditional planners. More importantly, it showed strong generalization: RoboBallet could adapt instantly to new factory layouts or recover if one robot failed, something previous methods struggled with. For manufacturers, this could mean faster deployment of automation, less downtime, and the ability to reconfigure production lines on the fly. Applications range from automotive welding to electronics assembly, and even large-scale construction. The current system focuses on reaching tasks, but the team plans to expand it to more complex operations like pick-and-place or painting. Here's the paper:

A robotic ballet! 🩰 Coordinating multiple robot arms on a busy factory floor is notoriously complex. Each arm needs to move without colliding with its neighbors or the surrounding equipment, and today that planning is still mostly done by hand, a process that takes specialists hundreds of hours. Researchers at UCL, Google DeepMind, and Intrinsic have introduced RoboBallet, a new AI system that tackles this challenge head-on. Using a combination of graph neural networks and reinforcement learning, RoboBallet learns how to coordinate many robots in real time, generating smooth, collision-free motion plans in seconds instead of days. In tests, the system handled up to 40 tasks with eight arms working together, far beyond the limits of traditional planners. More importantly, it showed strong generalization: RoboBallet could adapt instantly to new factory layouts or recover if one robot failed, something previous methods struggled with. For manufacturers, this could mean faster deployment of automation, less downtime, and the ability to reconfigure production lines on the fly. Applications range from automotive welding to electronics assembly, and even large-scale construction. The current system focuses on reaching tasks, but the team plans to expand it to more complex operations like pick-and-place or painting. Here's the paper:

Lukas Ziegler

26,083 次观看 • 1 年前

NeoFarm is using robotics to make organic market gardening profitable! 🪏 The French agri-tech startup has developed a patented system that automates the toughest parts of organic vegetable production, from soil prep to repetitive harvesting. On each farm, the system supports 20+ crop species grown in open ground without chemical fertilizers and with near-total water autonomy, a rare combination at this scale. 👩🏼‍🌾 By offloading heavy, repetitive tasks to its automation platform, NeoFarm reduces the physical strain on its 30-person market gardening teams, enabling consistent output with fewer labor bottlenecks. The model is replicable and modular, designed to be deployed directly on local farmers’ land, integrating with their expertise while bringing in robotic efficiency. Recently they secured over €30 million to scale up their operations! 💸

NeoFarm is using robotics to make organic market gardening profitable! 🪏 The French agri-tech startup has developed a patented system that automates the toughest parts of organic vegetable production, from soil prep to repetitive harvesting. On each farm, the system supports 20+ crop species grown in open ground without chemical fertilizers and with near-total water autonomy, a rare combination at this scale. 👩🏼‍🌾 By offloading heavy, repetitive tasks to its automation platform, NeoFarm reduces the physical strain on its 30-person market gardening teams, enabling consistent output with fewer labor bottlenecks. The model is replicable and modular, designed to be deployed directly on local farmers’ land, integrating with their expertise while bringing in robotic efficiency. Recently they secured over €30 million to scale up their operations! 💸

Lukas Ziegler

116,738 次观看 • 1 年前

A science fiction level breakthrough. MIT’s electrohydraulic fiber muscles bring robotic actuation closer to a biological level. A strand measuring only 2 millimeters in diameter has the same power density as human skeletal muscle. A 22-gram fiber bundle can lift 4 kilograms roughly 200 times its own weight. It responds in 0.3 seconds and operates silently without the humming of an electric motor or a bulky external hydraulic pump. The entire power system is embedded inside the fiber. Like yarn it can be woven bundled and wrapped around a robotic arm. When the robot shakes someone’s hand the fibers yield smoothly to reduce the force. This is more than a material upgrade. It represents a fundamental change in how robots are actuated. As robots move away from rigid geared motors and gain muscle structures closer to biological ones truly biomimetic humanoids move one major step closer. China has also had mature AI vision systems for some time. Ruigan Robotics uses self developed AI algorithms combined with dual-spectrum imaging fusion. The system responds within milliseconds and continues tracking a target even when it suddenly changes direction.

A science fiction level breakthrough. MIT’s electrohydraulic fiber muscles bring robotic actuation closer to a biological level. A strand measuring only 2 millimeters in diameter has the same power density as human skeletal muscle. A 22-gram fiber bundle can lift 4 kilograms roughly 200 times its own weight. It responds in 0.3 seconds and operates silently without the humming of an electric motor or a bulky external hydraulic pump. The entire power system is embedded inside the fiber. Like yarn it can be woven bundled and wrapped around a robotic arm. When the robot shakes someone’s hand the fibers yield smoothly to reduce the force. This is more than a material upgrade. It represents a fundamental change in how robots are actuated. As robots move away from rigid geared motors and gain muscle structures closer to biological ones truly biomimetic humanoids move one major step closer. China has also had mature AI vision systems for some time. Ruigan Robotics uses self developed AI algorithms combined with dual-spectrum imaging fusion. The system responds within milliseconds and continues tracking a target even when it suddenly changes direction.

Techniahqrobot | humanoid robots

50,254 次观看 • 2 个月前

The ability to heal is proof Life is Intelligently designed. Think about this. Without the ability to heal, the smallest injury would be devastating, even for the simplest single celled organism. A single cell that could not heal itself would not live long enough to evolve anything. Healing is a complex process that requires additional systems of specialized molecules and genetic information: sensors, triggers, guidance, regulation, etc. Without the whole system in place and fully functional, one tiny scratch becomes deadly. There is no step-by-step “almost healing” system that evolution & natural selection can build gradually. Healing only happens when all the parts are there working together. Cellular healing is a complex integrated system that had to be present in full from the start - not something that could have been assembled later by trial and error. The necessity and the complexity of the healing system points to a single known cause: Life was Divinely Designed.

The ability to heal is proof Life is Intelligently designed. Think about this. Without the ability to heal, the smallest injury would be devastating, even for the simplest single celled organism. A single cell that could not heal itself would not live long enough to evolve anything. Healing is a complex process that requires additional systems of specialized molecules and genetic information: sensors, triggers, guidance, regulation, etc. Without the whole system in place and fully functional, one tiny scratch becomes deadly. There is no step-by-step “almost healing” system that evolution & natural selection can build gradually. Healing only happens when all the parts are there working together. Cellular healing is a complex integrated system that had to be present in full from the start - not something that could have been assembled later by trial and error. The necessity and the complexity of the healing system points to a single known cause: Life was Divinely Designed.

Divinely Designed

21,363 次观看 • 7 天前

A Breakthrough in Robotics: Spherical Gears Enter Mass Production Spherical gears, the kind of joint that would allow a robot to move like a human shoulder, have been notoriously difficult to manufacture with high precision. That's changing, thanks to a new design and a path to mass production that could have a huge impact on robotics. The breakthrough comes from a new design called the ABENICS spherical gear, developed by researchers at Yamagata University. This innovative mechanism enables a joint to move in three degrees of freedom without the slippage issues of earlier designs. It achieves this by using a "cross-spherical gear" that meshes with one or more "monopole gears." Mass production is now on the horizon. Although the initial manufacturing of the gears was inefficient, Nissei Corporation improved the process and established the necessary technology. The companies Kanematsu and Nissei have now entered the marketing phase, with production expected to begin in 2027. The impact of this technology is significant. Mass-produced spherical gears are expected to enable highly versatile and efficient robotic limbs. ► Humanoid and Mobile Robots: The design allows for compact, high-torque ball joints ideal for creating versatile and efficient robotic limbs. ► Aerospace: Potential applications include deployment mechanisms for satellite solar panels. ► Other Industries: The technology is also being explored for its potential to enhance productivity in healthcare, nursing care, and restaurants.

A Breakthrough in Robotics: Spherical Gears Enter Mass Production Spherical gears, the kind of joint that would allow a robot to move like a human shoulder, have been notoriously difficult to manufacture with high precision. That's changing, thanks to a new design and a path to mass production that could have a huge impact on robotics. The breakthrough comes from a new design called the ABENICS spherical gear, developed by researchers at Yamagata University. This innovative mechanism enables a joint to move in three degrees of freedom without the slippage issues of earlier designs. It achieves this by using a "cross-spherical gear" that meshes with one or more "monopole gears." Mass production is now on the horizon. Although the initial manufacturing of the gears was inefficient, Nissei Corporation improved the process and established the necessary technology. The companies Kanematsu and Nissei have now entered the marketing phase, with production expected to begin in 2027. The impact of this technology is significant. Mass-produced spherical gears are expected to enable highly versatile and efficient robotic limbs. ► Humanoid and Mobile Robots: The design allows for compact, high-torque ball joints ideal for creating versatile and efficient robotic limbs. ► Aerospace: Potential applications include deployment mechanisms for satellite solar panels. ► Other Industries: The technology is also being explored for its potential to enhance productivity in healthcare, nursing care, and restaurants.

RoboHub🤖

384,888 次观看 • 1 年前

A rare insight into the stabilisation system of the Nike Ajax missile, deployed in the early Cold War around 1954 as part of the first operational radar-guided air defense network. Inside the guidance unit, the core was a high-speed mechanical gyro assembly spinning at roughly 20,000-30,000 RPM, using precision-machined rotors and air or fluid bearings to maintain inertial reference under extreme launch vibration. This gyro did not guide the missile directly, it acted as the stable reference frame that converted ground radar commands into precise attitude corrections. The missile itself used a powerful solid booster followed by a liquid sustainer, with cost per unit estimated in the $20,000, 1950s production scale for a system that could engage targets at 45 kms Video Source:- Inert Ordnance

A rare insight into the stabilisation system of the Nike Ajax missile, deployed in the early Cold War around 1954 as part of the first operational radar-guided air defense network. Inside the guidance unit, the core was a high-speed mechanical gyro assembly spinning at roughly 20,000-30,000 RPM, using precision-machined rotors and air or fluid bearings to maintain inertial reference under extreme launch vibration. This gyro did not guide the missile directly, it acted as the stable reference frame that converted ground radar commands into precise attitude corrections. The missile itself used a powerful solid booster followed by a liquid sustainer, with cost per unit estimated in the $20,000, 1950s production scale for a system that could engage targets at 45 kms Video Source:- Inert Ordnance

Ammanichanda

21,943 次观看 • 4 个月前

One tool to handle them all! 🧰 Traditional suction-based systems struggle with over 30% of SKUs. Mesh bags, loose apparel, and porous items often lead to failed picks or damaged goods. Nexera Robotics (Nexera Robotics) is pushing that ceiling to more than 95% by innovating the hardware, not just the software. Their solution? NeuraGrasp®. Instead of rigid fingers or air-dependent suction, NeuraGrasp uses a compliant membrane that conforms to any object. It creates a mechanical lock through friction and wrap-around contact, even on items that leak air or deform. Pressure is distributed by the material itself, meaning no complex force-feedback loops are needed to prevent crushing. It’s single tool can lift heavy payloads, yet pick a single peach without bruising it. A super important part is that no SKU-specific training and no tool changers required. The industry has spent years optimizing robot “brains” while ignoring the hands. Nexera is perfecting the touch to make robots more capable. Congrats Nexera Robotics team! 👏🏼 ~~ ♻️ Join the weekly robotics newsletter, and never miss any news →

One tool to handle them all! 🧰 Traditional suction-based systems struggle with over 30% of SKUs. Mesh bags, loose apparel, and porous items often lead to failed picks or damaged goods. Nexera Robotics (Nexera Robotics) is pushing that ceiling to more than 95% by innovating the hardware, not just the software. Their solution? NeuraGrasp®. Instead of rigid fingers or air-dependent suction, NeuraGrasp uses a compliant membrane that conforms to any object. It creates a mechanical lock through friction and wrap-around contact, even on items that leak air or deform. Pressure is distributed by the material itself, meaning no complex force-feedback loops are needed to prevent crushing. It’s single tool can lift heavy payloads, yet pick a single peach without bruising it. A super important part is that no SKU-specific training and no tool changers required. The industry has spent years optimizing robot “brains” while ignoring the hands. Nexera is perfecting the touch to make robots more capable. Congrats Nexera Robotics team! 👏🏼 ~~ ♻️ Join the weekly robotics newsletter, and never miss any news →

Lukas Ziegler

23,230 次观看 • 8 个月前

Westworld-like hand Suzhou-bassed Rochu Robotics just tested a biomimetic hand that is completely different from the rigid motor-driven dexterous hands on the market: Pneumatic/Fluid-driven artificial muscles + 1:1 human skeletal structure. These artificial muscles contract when pressurized,just like biological ones --pulling on biomimetic tendons to move the joints with smooth, natural motion. Just 4 biomimetic muscles can easily lift a 3kg kettlebell, and demonstrate the versatility of flexible grasping…while also acing fast finger challenges (peace sign, rock on, counting, etc.) almost matching a real human hand. True compliance and safety in human-robot interaction,no more cold, stiff mechanics. This one is developing real life-like movement logic.

Westworld-like hand Suzhou-bassed Rochu Robotics just tested a biomimetic hand that is completely different from the rigid motor-driven dexterous hands on the market: Pneumatic/Fluid-driven artificial muscles + 1:1 human skeletal structure. These artificial muscles contract when pressurized,just like biological ones --pulling on biomimetic tendons to move the joints with smooth, natural motion. Just 4 biomimetic muscles can easily lift a 3kg kettlebell, and demonstrate the versatility of flexible grasping…while also acing fast finger challenges (peace sign, rock on, counting, etc.) almost matching a real human hand. True compliance and safety in human-robot interaction,no more cold, stiff mechanics. This one is developing real life-like movement logic.

CyberRobo

28,240 次观看 • 3 个月前

This is WILD! MIT just solved one of the hardest unsolved problems in robotics (Save this). For decades, the fundamental problem with soft robots and wearable exoskeletons has not been compute or AI, it has been actuation. The moment you try to give a soft robot meaningful strength, you run into the same wall every engineer has hit since the field began, fluid-driven systems require external pumps, hydraulic reservoirs, and heavy infrastructure that makes the entire thing impractical to wear or embed into fabric. MIT's new Electrofluidic Fiber Muscles solve that problem by eliminating external infrastructure entirely. The key insight is electrohydrodynamic pumping using electric fields to generate pressure directly from electricity, with no moving parts, no motors, and no external fluid reservoir. The fibers are less than 2 millimeters thick, can be woven into fabric like ordinary textile, and operate in complete silence because nothing physically moves inside them, it is just ions propelling fluid through a closed circuit. The performance numbers published in Science Robotics are not conceptual, they are empirical results from actual hardware. These fibers achieve a power density of 50 watts per kilogram, matching skeletal muscle, with a contraction strain of 20% and a response time of 0.3 seconds. A single bundled configuration lifted 4 kilograms, 200 times its own weight while a separate configuration drove a robotic arm through a 40-degree bend compliant enough to safely complete a human handshake. Another configuration launched objects in under 100 milliseconds, which is faster than a human flinch reflex. The design mirrors biological muscle architecture in a way that prior artificial muscle approaches never achieved. The fibers are organized into antagonistic pairs, one contracts while the other extends, exactly like biceps and triceps and because the system runs in a closed loop, the relaxing fiber serves as the fluid reservoir for the contracting one, which is what allows the whole system to operate untethered with no external tank. The applications are not hypothetical but rather are the exact use cases the industry has been waiting years for the hardware to catch up to. Exoskeletons for physical labor, prosthetic limbs that move with the natural compliance of biological tissue, assistive garments for patients with motor disorders, and soft robots capable of safe physical contact with humans are all immediately unlocked by a muscle technology that is silent, lightweight, and weavable into clothing. The deeper significance is what this technology does when it meets the AI robotics wave that is already underway. Every major humanoid robot program, Figure, 1X, Boston Dynamics, Tesla Optimus is currently bottlenecked by the same hardware limitations these fibers address, actuators that are too rigid, too loud, too heavy, or too dependent on infrastructure to operate naturally alongside humans. Electrofluidic fiber muscles do not just solve a materials science problem but rather they remove one of the last physical barriers between robots that live in labs and robots that live in the world.

This is WILD! MIT just solved one of the hardest unsolved problems in robotics (Save this). For decades, the fundamental problem with soft robots and wearable exoskeletons has not been compute or AI, it has been actuation. The moment you try to give a soft robot meaningful strength, you run into the same wall every engineer has hit since the field began, fluid-driven systems require external pumps, hydraulic reservoirs, and heavy infrastructure that makes the entire thing impractical to wear or embed into fabric. MIT's new Electrofluidic Fiber Muscles solve that problem by eliminating external infrastructure entirely. The key insight is electrohydrodynamic pumping using electric fields to generate pressure directly from electricity, with no moving parts, no motors, and no external fluid reservoir. The fibers are less than 2 millimeters thick, can be woven into fabric like ordinary textile, and operate in complete silence because nothing physically moves inside them, it is just ions propelling fluid through a closed circuit. The performance numbers published in Science Robotics are not conceptual, they are empirical results from actual hardware. These fibers achieve a power density of 50 watts per kilogram, matching skeletal muscle, with a contraction strain of 20% and a response time of 0.3 seconds. A single bundled configuration lifted 4 kilograms, 200 times its own weight while a separate configuration drove a robotic arm through a 40-degree bend compliant enough to safely complete a human handshake. Another configuration launched objects in under 100 milliseconds, which is faster than a human flinch reflex. The design mirrors biological muscle architecture in a way that prior artificial muscle approaches never achieved. The fibers are organized into antagonistic pairs, one contracts while the other extends, exactly like biceps and triceps and because the system runs in a closed loop, the relaxing fiber serves as the fluid reservoir for the contracting one, which is what allows the whole system to operate untethered with no external tank. The applications are not hypothetical but rather are the exact use cases the industry has been waiting years for the hardware to catch up to. Exoskeletons for physical labor, prosthetic limbs that move with the natural compliance of biological tissue, assistive garments for patients with motor disorders, and soft robots capable of safe physical contact with humans are all immediately unlocked by a muscle technology that is silent, lightweight, and weavable into clothing. The deeper significance is what this technology does when it meets the AI robotics wave that is already underway. Every major humanoid robot program, Figure, 1X, Boston Dynamics, Tesla Optimus is currently bottlenecked by the same hardware limitations these fibers address, actuators that are too rigid, too loud, too heavy, or too dependent on infrastructure to operate naturally alongside humans. Electrofluidic fiber muscles do not just solve a materials science problem but rather they remove one of the last physical barriers between robots that live in labs and robots that live in the world.

Milk Road AI

1,208,301 次观看 • 4 个月前

Dexterous hands are one of the biggest challenges in robotics, with even Elon Musk noting their development accounts for half of a humanoid robot's total work. A new approach from the Y-Hand M1 bionic hand may be a significant step forward. Based on an international first-of-its-kind "bionic tension-compression theory," the M1 replaces traditional rigid hinges with a 6-DoF joint system and uses self-developed magnetic artificial muscles. This design allows it to perform complex, human-like tasks, including: ► Mastering all 33 Feix dexterous grasp categories. ► Precisely twirling playing cards and threading a needle with subtle human-like adjustments. ► Smoothly twisting bottle caps and turning book pages. The team behind the M1 is already working on the next-gen Y-Hand M3, aiming for around 70 degrees of freedom, believing that robotic hands may soon reach or even exceed human-level dexterity.

Dexterous hands are one of the biggest challenges in robotics, with even Elon Musk noting their development accounts for half of a humanoid robot's total work. A new approach from the Y-Hand M1 bionic hand may be a significant step forward. Based on an international first-of-its-kind "bionic tension-compression theory," the M1 replaces traditional rigid hinges with a 6-DoF joint system and uses self-developed magnetic artificial muscles. This design allows it to perform complex, human-like tasks, including: ► Mastering all 33 Feix dexterous grasp categories. ► Precisely twirling playing cards and threading a needle with subtle human-like adjustments. ► Smoothly twisting bottle caps and turning book pages. The team behind the M1 is already working on the next-gen Y-Hand M3, aiming for around 70 degrees of freedom, believing that robotic hands may soon reach or even exceed human-level dexterity.

RoboHub🤖

64,560 次观看 • 1 年前

Teaching robots real dexterity has always been a challenge. But what if they could handle tools like a human? DexterityGen (DexGen) is a new system that helps robots use their hands better. It improves how they grip, move, and handle objects… from holding a pen to using a screwdriver. DexGen learns in simulation and refines its skills in the real world, making robotic hands much more useful. What makes DexGen special? ✅ Smarter movements that refine rough actions into precise skills ✅ Trained on a massive collection of dexterous tasks for better learning ✅ Better teleoperation that makes robotic hand control easier and safer ✅ Handles real-world challenges like small objects, tricky angles, and gravity This moves robots closer to real dexterity. It makes tool use more natural, improves stability, and brings robotic hands one step closer to human-level skill. Seen at Zhao-Heng Yin 🫶 Github: Paper:

Teaching robots real dexterity has always been a challenge. But what if they could handle tools like a human? DexterityGen (DexGen) is a new system that helps robots use their hands better. It improves how they grip, move, and handle objects… from holding a pen to using a screwdriver. DexGen learns in simulation and refines its skills in the real world, making robotic hands much more useful. What makes DexGen special? ✅ Smarter movements that refine rough actions into precise skills ✅ Trained on a massive collection of dexterous tasks for better learning ✅ Better teleoperation that makes robotic hand control easier and safer ✅ Handles real-world challenges like small objects, tricky angles, and gravity This moves robots closer to real dexterity. It makes tool use more natural, improves stability, and brings robotic hands one step closer to human-level skill. Seen at Zhao-Heng Yin 🫶 Github: Paper:

Ilir Aliu

51,526 次观看 • 1 年前

The machines Randall describes operate on a principle that connects directly to his broader research into plasma and toroidal geometry. Microscopic cavitation bubbles are generated and subjected to rapid alternating cycles of vacuum and pressure - produced naturally by the up and down motion of pistons in any conventional engine configuration. The compression phase and vacuum phase act on those bubbles in sequence, and what happens next is the detail Randall finds significant. The cavitation bubbles collapse on their axes and form perfect torus shapes - spontaneously, consistently, and in a way that initiates the same plasma self-organization process he has been tracing across ancient energy systems and sacred geometry traditions. The practical implication is that these toroidal plasma voids can be harvested directly from the machine producing them. Randall points to the vortex tube as a concrete demonstration of the underlying physics - a device that accepts air at room temperature and separates it into two counter-rotating vortices, one inside the other, spinning in opposite directions. The result is a temperature differential of up to several hundred degrees between the hot and cold ends, produced without any additional energy input. Randall’s argument is that this is not an isolated engineering curiosity. It is a visible, reproducible demonstration of the same principles that ancient plasma-based energy systems were built around - and that the machines now being developed around cavitation and toroidal geometry may be the closest modern technology has come to recovering what was lost.

The machines Randall describes operate on a principle that connects directly to his broader research into plasma and toroidal geometry. Microscopic cavitation bubbles are generated and subjected to rapid alternating cycles of vacuum and pressure - produced naturally by the up and down motion of pistons in any conventional engine configuration. The compression phase and vacuum phase act on those bubbles in sequence, and what happens next is the detail Randall finds significant. The cavitation bubbles collapse on their axes and form perfect torus shapes - spontaneously, consistently, and in a way that initiates the same plasma self-organization process he has been tracing across ancient energy systems and sacred geometry traditions. The practical implication is that these toroidal plasma voids can be harvested directly from the machine producing them. Randall points to the vortex tube as a concrete demonstration of the underlying physics - a device that accepts air at room temperature and separates it into two counter-rotating vortices, one inside the other, spinning in opposite directions. The result is a temperature differential of up to several hundred degrees between the hot and cold ends, produced without any additional energy input. Randall’s argument is that this is not an isolated engineering curiosity. It is a visible, reproducible demonstration of the same principles that ancient plasma-based energy systems were built around - and that the machines now being developed around cavitation and toroidal geometry may be the closest modern technology has come to recovering what was lost.

Randall Carlson

22,749 次观看 • 6 个月前