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From day one, mimic has been focused on a single goal: general-purpose dexterous manipulation. Today we're proud to announce the mimic hand M1 and the mimic wearable U1. We believe the only way to solve dexterous manipulation at scale is by going full-stack at the frontier of physical AI,... show more

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90,648 views • 18 days ago •via X (Twitter)

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Mimic Robotics released a full-stack dexterity platform: the mimic hand M1 + umimic (U1) wearable. They keep human hand morphology consistent across the entire data-model-dexterous hand-manipulation pipeline--from video pre-training to wearable demos and robot deployment. This avoids cross-embodiment gaps and captures the essence of upper-limb intelligence. M1: Tendon-driven (15 active DoF), highly backdrivable ( 25kg grasp, industrial-grade, Swiss-made. U1 lets humans teach the robot naturally with their own hands--1:1 kinematics and sensing match, no latency or retargeting, enabling higher-quality and more scalable data. Looking forward to its performance at the customer site.

Mimic Robotics released a full-stack dexterity platform: the mimic hand M1 + umimic (U1) wearable. They keep human hand morphology consistent across the entire data-model-dexterous hand-manipulation pipeline--from video pre-training to wearable demos and robot deployment. This avoids cross-embodiment gaps and captures the essence of upper-limb intelligence. M1: Tendon-driven (15 active DoF), highly backdrivable ( 25kg grasp, industrial-grade, Swiss-made. U1 lets humans teach the robot naturally with their own hands--1:1 kinematics and sensing match, no latency or retargeting, enabling higher-quality and more scalable data. Looking forward to its performance at the customer site.

CyberRobo

26,160 views • 16 days ago

Happy to announce mimic-one: a Scalable Model Recipe for General Purpose Robot Dexterity, the culmination of years of research work in dexterous manipulation with imitation learning.

Happy to announce mimic-one: a Scalable Model Recipe for General Purpose Robot Dexterity, the culmination of years of research work in dexterous manipulation with imitation learning.

Elvis Nava

20,238 views • 1 year ago

The Clone hand is a compact, biomimetic robotic hand designed to mimic human anatomy and perform a diverse array of manipulation tasks. Credit: Clone Robotics

The Clone hand is a compact, biomimetic robotic hand designed to mimic human anatomy and perform a diverse array of manipulation tasks. Credit: Clone Robotics

Tech Burrito

13,799 views • 1 year ago

Imitation learning has a data scarcity problem. Introducing EgoDex from Apple, the largest and most diverse dataset of dexterous human manipulation to date — 829 hours of egocentric video + paired 3D hand poses across 194 tasks. Now on arxiv: (1/4)

Imitation learning has a data scarcity problem. Introducing EgoDex from Apple, the largest and most diverse dataset of dexterous human manipulation to date — 829 hours of egocentric video + paired 3D hand poses across 194 tasks. Now on arxiv: (1/4)

Ryan Hoque

114,164 views • 1 year ago

“Dexterous capability is directly proportional to the size of the addressable market for general-purpose humanoid robots,” says James Wells, interim CEO and CCO. Sanctuary AI announces its latest technical milestone using hydraulic actuation, opening up a wide range of industrial and high value work tasks that require fine manipulation. #AI #Robotics

“Dexterous capability is directly proportional to the size of the addressable market for general-purpose humanoid robots,” says James Wells, interim CEO and CCO. Sanctuary AI announces its latest technical milestone using hydraulic actuation, opening up a wide range of industrial and high value work tasks that require fine manipulation. #AI #Robotics

Sanctuary AI

16,583 views • 1 year ago

Pretty hand👋 just like a real human hand. Hangzhou Xynova unveils the Flex 2 Hybrid-Drive Dexterous Hand (Cable-Driven + Direct-Driven). Tactile Perception, and the camera is positioned at the wrist joint rather than in the center of the palm. They will showcase the physical hand at ICRA 2026 in Vienna. (Humans have continuously replicated the hand that evolved two million years ago, while attempting to coordinate hand and brain.)

Pretty hand👋 just like a real human hand. Hangzhou Xynova unveils the Flex 2 Hybrid-Drive Dexterous Hand (Cable-Driven + Direct-Driven). Tactile Perception, and the camera is positioned at the wrist joint rather than in the center of the palm. They will showcase the physical hand at ICRA 2026 in Vienna. (Humans have continuously replicated the hand that evolved two million years ago, while attempting to coordinate hand and brain.)

CyberRobo

75,101 views • 2 months ago

Can a dexterous hand still function after being run over by a 2-ton car? The dexterous hand is the most expensive component of a humanoid robot, and if it breaks, the task is interrupted. Hangzhou BrainCo conducted a rigorous test on its latest dexterous hand, Revo2: it was run over by a nearly 2-ton Volvo car, dropped from a height of 5m, dropped 30m, and subjected to forceful impacts from a Unitree G1 robot. It still managed to maintain a stable grip and continue operating. Revo2 is BrainCo's next-generation dexterous/bionic hand, released last year. yes, a human-robot hybrid hand. It's very light, only 383g, 20kg payload,capable of precision manipulation down to 0.1mm (such as threading a needle), and possesses multi-dimensional tactile perception (hardness, texture, direction, proximity, etc.). This test also demonstrates that after achieving breakthroughs in performance, a dexterous hand also needs to be extremely durable and able to function under extreme environmental pressures.

Can a dexterous hand still function after being run over by a 2-ton car? The dexterous hand is the most expensive component of a humanoid robot, and if it breaks, the task is interrupted. Hangzhou BrainCo conducted a rigorous test on its latest dexterous hand, Revo2: it was run over by a nearly 2-ton Volvo car, dropped from a height of 5m, dropped 30m, and subjected to forceful impacts from a Unitree G1 robot. It still managed to maintain a stable grip and continue operating. Revo2 is BrainCo's next-generation dexterous/bionic hand, released last year. yes, a human-robot hybrid hand. It's very light, only 383g, 20kg payload,capable of precision manipulation down to 0.1mm (such as threading a needle), and possesses multi-dimensional tactile perception (hardness, texture, direction, proximity, etc.). This test also demonstrates that after achieving breakthroughs in performance, a dexterous hand also needs to be extremely durable and able to function under extreme environmental pressures.

CyberRobo

45,434 views • 5 months ago

Happy to share what I’ve been working on since joining Genesis! GENE-26.5 is a one-of-a-kind, robotics-native multimodal foundation model that learns from diverse, in-the-wild data across modalities and outputs actions enabling a 54-DoF robot system to perform the most dexterous, long-horizon manipulation tasks to date—approaching human-level capability. This is the result of innovations across the full stack—data collection and processing, robot systems, model architecture, training strategies, and scalable evaluation infrastructure.

Happy to share what I’ve been working on since joining Genesis! GENE-26.5 is a one-of-a-kind, robotics-native multimodal foundation model that learns from diverse, in-the-wild data across modalities and outputs actions enabling a 54-DoF robot system to perform the most dexterous, long-horizon manipulation tasks to date—approaching human-level capability. This is the result of innovations across the full stack—data collection and processing, robot systems, model architecture, training strategies, and scalable evaluation infrastructure.

Zu Wang

19,493 views • 2 months ago

Tactile feedback is one of the most important modalities in manipulation, but has been underutilized in dexterous hands. T-Dex is a framework for learning dexterous policies from tactile play data, beating vision and torque-based methods by 1.7x. 🧵👇

Tactile feedback is one of the most important modalities in manipulation, but has been underutilized in dexterous hands. T-Dex is a framework for learning dexterous policies from tactile play data, beating vision and torque-based methods by 1.7x. 🧵👇

Lerrel Pinto

84,611 views • 3 years ago

Teaching robots to perform dexterous manipulation tasks currently requires teleoperation, which limits demonstration quality, speed, and scalability. Instead, why not use human videos? The problem is that a human hand isn’t a robot hand, so data must be retargeted using simulation to resolve issues like collisions and interpenetration when controlling the hand. In VideoManip, Hongyi Chen and co-authors built a system to solve this problem, taking in RGB videos of humans performing manipulation tasks and using them to create accurate simulations with which to learn robot policies. Watch episode #73 of RoboPapers, hosted by Michael Cho - Rbt/Acc and Chris Paxton, now to learn more!

Teaching robots to perform dexterous manipulation tasks currently requires teleoperation, which limits demonstration quality, speed, and scalability. Instead, why not use human videos? The problem is that a human hand isn’t a robot hand, so data must be retargeted using simulation to resolve issues like collisions and interpenetration when controlling the hand. In VideoManip, Hongyi Chen and co-authors built a system to solve this problem, taking in RGB videos of humans performing manipulation tasks and using them to create accurate simulations with which to learn robot policies. Watch episode #73 of RoboPapers, hosted by Michael Cho - Rbt/Acc and Chris Paxton, now to learn more!

RoboPapers

27,344 views • 3 months ago

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🤖

62,997 views • 10 months ago

Learning dexterous policies from human videos is challenging due to differences between human and robot hands. We present HuDOR, a method that learns dexterous policies within the robot's physical constraints using just one human video and an hour of online interactions! [1/n]

Learning dexterous policies from human videos is challenging due to differences between human and robot hands. We present HuDOR, a method that learns dexterous policies within the robot's physical constraints using just one human video and an hour of online interactions! [1/n]

Irmak Guzey

65,121 views • 1 year ago

Open-Source Robotic Hand That Costs Just $300. California-based company TetherIA.ai has officially launched its open-source robotic hand, the Aero Hand Open. Designed to be the most capable at the lowest cost, this hand is a new tool for embodied AI research. In the clip, it demonstrates impressive dexterity by grasping an M5 screw, picking up an iPhone, and opening a soda can. Key Features: ► Price: $314.00 ► Open Source: CAD, electronics, and firmware are all open source. ► Actuation: 7 Active Degrees of Freedom (16 joints) with a tendon-driven design. ► Weight: Under 400 grams. ► Purpose: Built for embodied AI research to make dexterous manipulation accessible to all. For more details and to purchase:

Open-Source Robotic Hand That Costs Just $300. California-based company TetherIA.ai has officially launched its open-source robotic hand, the Aero Hand Open. Designed to be the most capable at the lowest cost, this hand is a new tool for embodied AI research. In the clip, it demonstrates impressive dexterity by grasping an M5 screw, picking up an iPhone, and opening a soda can. Key Features: ► Price: $314.00 ► Open Source: CAD, electronics, and firmware are all open source. ► Actuation: 7 Active Degrees of Freedom (16 joints) with a tendon-driven design. ► Weight: Under 400 grams. ► Purpose: Built for embodied AI research to make dexterous manipulation accessible to all. For more details and to purchase:

RoboHub🤖

45,830 views • 10 months ago

Can robotic hands really outperform human dexterity? Meet the Linker Hand L30 from LinkerBot. This tendon-driven dexterous hand packs high precision and compact size, making it a serious contender for complex manipulation tasks: ► 22 Degrees of Freedom utilizing a sophisticated tendon drive system. ► Ultra-fine positioning control with ±0.20mm repeatable accuracy. ► Rapid response speed, achieving up to 450°/S for core movements. ► Adaptive grasping enabled by high-sensitivity tactile sensors built into the fingertips. ► Compact dimensions (85mm average width, 179mm length) despite its complex architecture.

Can robotic hands really outperform human dexterity? Meet the Linker Hand L30 from LinkerBot. This tendon-driven dexterous hand packs high precision and compact size, making it a serious contender for complex manipulation tasks: ► 22 Degrees of Freedom utilizing a sophisticated tendon drive system. ► Ultra-fine positioning control with ±0.20mm repeatable accuracy. ► Rapid response speed, achieving up to 450°/S for core movements. ► Adaptive grasping enabled by high-sensitivity tactile sensors built into the fingertips. ► Compact dimensions (85mm average width, 179mm length) despite its complex architecture.

RoboHub🤖

22,556 views • 10 months ago

Introducing FLUX-mimic, a next-generation Video-Action Model for general purpose dexterity, developed in partnership with Black Forest Labs. Late last year we published mimic-video and introduced Video-Action Models (VAM): a new family of robotics foundation models built on top of video generation models. We showed that robot control reduces to visual prediction, and that robot capability is downstream of improvements in video modeling accuracy. The obvious implication was that advances in the video modeling frontier would directly translate to increased capabilities in end-to-end robot learning. FLUX-mimic is that thesis at frontier scale: We've applied our VAM architecture to the strongest video backbone available today, FLUX 3 from Black Forest Labs, and trained it on data from our own robots and wearables. General-purpose dexterity, running on a single GPU on premises. Because the model already understands world dynamics, it needs far fewer demonstrations to learn a new task. This is game-changing for our mission to deploy robots to factory floors, where industrial robot data is scarce and expensive to collect. We're now testing and deploying FLUX-mimic with manufacturing leaders like Audi USA, on complex, multi-step manipulation long considered impossible for conventional automation.

Introducing FLUX-mimic, a next-generation Video-Action Model for general purpose dexterity, developed in partnership with Black Forest Labs. Late last year we published mimic-video and introduced Video-Action Models (VAM): a new family of robotics foundation models built on top of video generation models. We showed that robot control reduces to visual prediction, and that robot capability is downstream of improvements in video modeling accuracy. The obvious implication was that advances in the video modeling frontier would directly translate to increased capabilities in end-to-end robot learning. FLUX-mimic is that thesis at frontier scale: We've applied our VAM architecture to the strongest video backbone available today, FLUX 3 from Black Forest Labs, and trained it on data from our own robots and wearables. General-purpose dexterity, running on a single GPU on premises. Because the model already understands world dynamics, it needs far fewer demonstrations to learn a new task. This is game-changing for our mission to deploy robots to factory floors, where industrial robot data is scarce and expensive to collect. We're now testing and deploying FLUX-mimic with manufacturing leaders like Audi USA, on complex, multi-step manipulation long considered impossible for conventional automation.

mimic

114,454 views • 11 days ago

Y-Hand M1:universal hand for intelligent humanoid robots the humanoid dexterous hand with the highest degrees of freedom, developed by Yuequan Bionic Slide the pen, open the bottle, cut the paper, handle the trivial matters like a human, and soon it will be connected to the humanoid robot to become a factory operator, elderly care and home assistant. »38 DOF, 28.7k load capacity »Fingertip repeat positioning accuracy of 0.04 mm »Five-finger closure in just 0.2 seconds »Replicates human finger joints with self-developed magnetoelectric-driven artificial muscles

Y-Hand M1:universal hand for intelligent humanoid robots the humanoid dexterous hand with the highest degrees of freedom, developed by Yuequan Bionic Slide the pen, open the bottle, cut the paper, handle the trivial matters like a human, and soon it will be connected to the humanoid robot to become a factory operator, elderly care and home assistant. »38 DOF, 28.7k load capacity »Fingertip repeat positioning accuracy of 0.04 mm »Five-finger closure in just 0.2 seconds »Replicates human finger joints with self-developed magnetoelectric-driven artificial muscles

CyberRobo

14,341 views • 10 months ago

Hands are as important as the brain. From Shenzhen, Stella Robot has unveiled the PANTHEON HAND 22:a new generation of bionic dexterous hand that combines 22 degrees of freedom with remarkable strength and finesse. It’s a hand that truly understands precision. It can lift 30 kilograms, yet is delicate enough to thread a needle.Each finger can bear 1.5 kilograms, and the entire hand can gently hold a piece of tofu or sense the subtle expansion of a balloon. Powered by a tendon-driven mechanism with integrated actuators inside the forearm, it achieves compact design and natural, human-like movement. From precision assembly and component handling to material transport and human-robot collaboration,the PANTHEON HAND 22 shows what it means for humanoid robots to truly work with their hands.

Hands are as important as the brain. From Shenzhen, Stella Robot has unveiled the PANTHEON HAND 22:a new generation of bionic dexterous hand that combines 22 degrees of freedom with remarkable strength and finesse. It’s a hand that truly understands precision. It can lift 30 kilograms, yet is delicate enough to thread a needle.Each finger can bear 1.5 kilograms, and the entire hand can gently hold a piece of tofu or sense the subtle expansion of a balloon. Powered by a tendon-driven mechanism with integrated actuators inside the forearm, it achieves compact design and natural, human-like movement. From precision assembly and component handling to material transport and human-robot collaboration,the PANTHEON HAND 22 shows what it means for humanoid robots to truly work with their hands.

CyberRobo

26,867 views • 9 months ago

Genesis AI has stepped into the spotlight The company is a SF Bay Area-based full-stack embodied AI startup. The Stack - Foundation model - 20 DoF dexterous hand - Tactile-sensing data-collection glove + Data engine - Custom motor controllers - In-house high-fidelity simulator The Thesis: Manipulation is a system problem, not just an AI problem. The company’s first general-purpose robot is teased as the “ultimate culmination” of the stack. Founders Zhou Xian (CEO) and Théophile Gervet (President), formerly of Mistral, NVIDIA, Google, CMU, MIT, and Stanford. $105 million raised in July 2025. Dual headquarters in San Carlos, CA and Paris.

Genesis AI has stepped into the spotlight The company is a SF Bay Area-based full-stack embodied AI startup. The Stack - Foundation model - 20 DoF dexterous hand - Tactile-sensing data-collection glove + Data engine - Custom motor controllers - In-house high-fidelity simulator The Thesis: Manipulation is a system problem, not just an AI problem. The company’s first general-purpose robot is teased as the “ultimate culmination” of the stack. Founders Zhou Xian (CEO) and Théophile Gervet (President), formerly of Mistral, NVIDIA, Google, CMU, MIT, and Stanford. $105 million raised in July 2025. Dual headquarters in San Carlos, CA and Paris.

The Humanoid Hub

49,931 views • 2 months ago

How to chain multiple dexterous skills to tackle complex long-horizon manipulation tasks? Imagine retrieving a LEGO block from a pile, rotating it in-hand, and inserting it at the desired location to build a structure. Introducing our new work - Sequential Dexterity 🧵👇

How to chain multiple dexterous skills to tackle complex long-horizon manipulation tasks? Imagine retrieving a LEGO block from a pile, rotating it in-hand, and inserting it at the desired location to build a structure. Introducing our new work - Sequential Dexterity 🧵👇

Chen Wang

159,809 views • 2 years ago

🚨 BREAKING: Swiss startup mimic just raised €13.8M to teach robots the one thing they still struggle with human-like dexterity. 🇨🇭 The Zurich-based company is developing physical AI systems that allow robots to learn directly from human demonstrations. Skilled operators wear custom motion-tracking gear on real factory floors, generating data that trains robots to grasp, move, and adapt with human precision. Founded in 2024 as a spin-off from ETH Zurich, mimic pairs AI-driven dexterous robotic hands with standard industrial robot arms, skipping the humanoid form factor in favor of practical, deployable automation. The oversubscribed seed round was led by Elaia with participation from Speedinvest, Founderful, 1st Kind, 10x Founders, 2100 Ventures, and the Sequoia Scout Fund, bringing total funding to over $20M. Their technology is already being piloted with Fortune 500 manufacturers and logistics operators, where robots are learning complex manipulation tasks once reserved for humans. Why it matters: Europe is stepping up in the AI robotics race. By making dexterity scalable, mimic bridges the gap between lab breakthroughs and real factory deployment, where automation still meets its hardest challenges. As CEO Stefan Weirich put it: “We make dexterity deployable at scale, closing the gap between what AI can do in the lab and what factories actually need.” Let's go robotics in Europe! 🔥

🚨 BREAKING: Swiss startup mimic just raised €13.8M to teach robots the one thing they still struggle with human-like dexterity. 🇨🇭 The Zurich-based company is developing physical AI systems that allow robots to learn directly from human demonstrations. Skilled operators wear custom motion-tracking gear on real factory floors, generating data that trains robots to grasp, move, and adapt with human precision. Founded in 2024 as a spin-off from ETH Zurich, mimic pairs AI-driven dexterous robotic hands with standard industrial robot arms, skipping the humanoid form factor in favor of practical, deployable automation. The oversubscribed seed round was led by Elaia with participation from Speedinvest, Founderful, 1st Kind, 10x Founders, 2100 Ventures, and the Sequoia Scout Fund, bringing total funding to over $20M. Their technology is already being piloted with Fortune 500 manufacturers and logistics operators, where robots are learning complex manipulation tasks once reserved for humans. Why it matters: Europe is stepping up in the AI robotics race. By making dexterity scalable, mimic bridges the gap between lab breakthroughs and real factory deployment, where automation still meets its hardest challenges. As CEO Stefan Weirich put it: “We make dexterity deployable at scale, closing the gap between what AI can do in the lab and what factories actually need.” Let's go robotics in Europe! 🔥

Lukas Ziegler

77,152 views • 9 months ago