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Holy…S😳 Xiaomi's New CyberOne is so human-like Although this update features a bionic hand, I was immediately drawn to it. Let's look at the changes in the hand： It can handle industrial precision tasks like turning screws, plus delicate operations such as pinching feathers and throwing balloons. Behind the...

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CyberRobo

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111,430 次观看 • 5 个月前 •via X (Twitter)

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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.
0:53

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 次观看 • 10 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.
0:28

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 • 11 个月前

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.
1:17

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 次观看 • 6 个月前

AgiBot has formally unveiled its G2 humanoid robot, a system designed to transition into various industries and liberate humans from repetitive labor. G2 features high-performance joints, precision torque sensors, and an advanced spatial perception system, supporting quick deployment and multi-modal voice interaction. ► Factory Floor Performance: The G2 is engineered to industrial standards. In a safety belt lock production line, robots collaborate with human workers, performing tasks like pressing lock cores. The G2 collects production data to continuously train and iterate models (local server deployment ensures data privacy), steadily improving its operational ability. ► Mobility & Safety: The G2 navigates narrow factory aisles using dual LiDAR and full-panorama vision for environment sensing and collision detection. Its chassis is designed to overcome common obstacles (speed bumps, elevator gaps). It supports 24/7 continuous operation via autonomous return-to-charge and battery swapping. ► Humanoid Design Advantage: The G2's design includes a three-degree-of-freedom flexible waist, allowing it to mimic natural human movements like bending and side-leaning. This dramatically expands its operational workspace and enables seamless integration into existing human-centric production lines without costly modifications. ► Advanced Dexterity & Learning (Lab): The new G02 arm is the world's first cross-moment arm, featuring high-precision joint torque sensors that allow it to precisely sense external forces and adjust stiffness, mimicking human hand compliance. Using Real-Machine Reinforcement Learning (RL), the G2 can learn complex, delicate tasks like memory stick insertion in about one hour with minimal human intervention. ► Logistics & Grasping: In logistics sorting, the G2 uses a 19-degree-of-freedom mechanical dexterous hand (20N maximum fingertip force; 35kg capacity for hard objects) equipped with 3D tactile sensors to ensure it grasps securely without damaging items. Its full-body articulation (waist and legs) aids grasping and posture adjustment. ► Model & Data: G2's intelligence is powered by the Go-One Large Embodied Model (VLA architecture: Vision-Language-Latent Action) and the GE-One World Model (vision-centric predictive modeling), trained using the AgiBot Word true-machine dataset (over 500k downloads). ► Service & Interaction: The G2 is deployed as a guide/receptionist in settings like art museums. It uses its high-DOF head, arms, and waist to point to exhibits, maintains eye contact while navigating difficult spaces (chassis walks forward, body faces backward), handles specialized and random queries, and uses proactive safety features (stops movement, issues warnings) when people get too close.
2:49

AgiBot has formally unveiled its G2 humanoid robot, a system designed to transition into various industries and liberate humans from repetitive labor. G2 features high-performance joints, precision torque sensors, and an advanced spatial perception system, supporting quick deployment and multi-modal voice interaction. ► Factory Floor Performance: The G2 is engineered to industrial standards. In a safety belt lock production line, robots collaborate with human workers, performing tasks like pressing lock cores. The G2 collects production data to continuously train and iterate models (local server deployment ensures data privacy), steadily improving its operational ability. ► Mobility & Safety: The G2 navigates narrow factory aisles using dual LiDAR and full-panorama vision for environment sensing and collision detection. Its chassis is designed to overcome common obstacles (speed bumps, elevator gaps). It supports 24/7 continuous operation via autonomous return-to-charge and battery swapping. ► Humanoid Design Advantage: The G2's design includes a three-degree-of-freedom flexible waist, allowing it to mimic natural human movements like bending and side-leaning. This dramatically expands its operational workspace and enables seamless integration into existing human-centric production lines without costly modifications. ► Advanced Dexterity & Learning (Lab): The new G02 arm is the world's first cross-moment arm, featuring high-precision joint torque sensors that allow it to precisely sense external forces and adjust stiffness, mimicking human hand compliance. Using Real-Machine Reinforcement Learning (RL), the G2 can learn complex, delicate tasks like memory stick insertion in about one hour with minimal human intervention. ► Logistics & Grasping: In logistics sorting, the G2 uses a 19-degree-of-freedom mechanical dexterous hand (20N maximum fingertip force; 35kg capacity for hard objects) equipped with 3D tactile sensors to ensure it grasps securely without damaging items. Its full-body articulation (waist and legs) aids grasping and posture adjustment. ► Model & Data: G2's intelligence is powered by the Go-One Large Embodied Model (VLA architecture: Vision-Language-Latent Action) and the GE-One World Model (vision-centric predictive modeling), trained using the AgiBot Word true-machine dataset (over 500k downloads). ► Service & Interaction: The G2 is deployed as a guide/receptionist in settings like art museums. It uses its high-DOF head, arms, and waist to point to exhibits, maintains eye contact while navigating difficult spaces (chassis walks forward, body faces backward), handles specialized and random queries, and uses proactive safety features (stops movement, issues warnings) when people get too close.

RoboHub🤖

46,733 次观看 • 10 个月前

China unveils humanoid robot with lifelike skin and blinking eyes built for daily life | Prabhat Ranjan Mishra, Interesting Engineering Large Language Models (LLMs) and Vision-Language Models (VLMs) help process and interpret complex data from human interactions. A Shanghai-based company has developed humanoid robots that appear as real as humans. The advanced bionic humanoid robot is integrated with self-supervised AI algorithms. Named Elf V1, the robot can perceive the world, communicate, learn, and interact intelligently with its surroundings. Developed by AheadForm Technology, the robot offers up to 30 degrees of freedom, powered by a precise control system and an advanced AI learning algorithm. Robot offers expressive facial features The robot offers expressive facial features, moving eyes, and synchronized speech. It can also convey emotions and understand human non-verbal cues, making interactions more natural and engaging. The robot has highly interactive capabilities and lifelike appearances. AheadForm expects that its robots could soon seamlessly integrate into daily life, providing assistance, companionship, and support across various industries. “We believe that by developing realistic and expressive robot heads, we can bridge the gap between humans and machines, fostering a new era of interactive and intelligent robotics,” said the company in a statement. Reports revealed that to avoid the “uncanny valley” effect and be able to interact with us, they are given lifelike skin and capabilities to read our emotions and respond appropriately using dynamic expression simulation and emotion generation tech. Bionic skin and high-precision control system The Elf V1 series of humanoids features 30 facial muscles animated by brushless micro-motors and managed by a high-precision control system. Paired with an ability to detect their users’ emotions with low latency and bionic skin, their facial expressions are nearly identical to those of humans, reported CGTN. The company claims it’s pioneering the development of realistic humanoid robots designed to revolutionize human-robot interaction. It’s enhancing sophisticated humanoid robot heads that can express emotions, perceive their environment, and interact seamlessly with humans. By combining cutting-edge AI and advanced robotics, AheadForm aims to bring life to machines and transform how humans engage with technology. AI models boost robots’ responsiveness Seamless integration of Large Language Models (LLMs) and Vision-Language Models (VLMs) into the humanoid robots can help them process and interpret complex data from human interactions, enabling the robot to learn and adapt in real-time, achieving human-level understanding and responsiveness. AheadForm uses Brushless Motors that deliver ultra-quiet operation and high responsiveness, specifically designed for precision facial movements in humanoid robots. With its compact size, lightweight design, and energy efficiency, this motor is the ideal choice for next-generation robots that require precise, subtle facial control to create a truly human-like experience. Previously, the company unveiled the Lan Series that features realistic humanoid robots with soft skin and 10 degrees of freedom, offering a lifelike appearance and intuitive movements. This series is designed for cost-efficiency, for applications prioritizing mobility and manipulation.
1:06

China unveils humanoid robot with lifelike skin and blinking eyes built for daily life | Prabhat Ranjan Mishra, Interesting Engineering Large Language Models (LLMs) and Vision-Language Models (VLMs) help process and interpret complex data from human interactions. A Shanghai-based company has developed humanoid robots that appear as real as humans. The advanced bionic humanoid robot is integrated with self-supervised AI algorithms. Named Elf V1, the robot can perceive the world, communicate, learn, and interact intelligently with its surroundings. Developed by AheadForm Technology, the robot offers up to 30 degrees of freedom, powered by a precise control system and an advanced AI learning algorithm. Robot offers expressive facial features The robot offers expressive facial features, moving eyes, and synchronized speech. It can also convey emotions and understand human non-verbal cues, making interactions more natural and engaging. The robot has highly interactive capabilities and lifelike appearances. AheadForm expects that its robots could soon seamlessly integrate into daily life, providing assistance, companionship, and support across various industries. “We believe that by developing realistic and expressive robot heads, we can bridge the gap between humans and machines, fostering a new era of interactive and intelligent robotics,” said the company in a statement. Reports revealed that to avoid the “uncanny valley” effect and be able to interact with us, they are given lifelike skin and capabilities to read our emotions and respond appropriately using dynamic expression simulation and emotion generation tech. Bionic skin and high-precision control system The Elf V1 series of humanoids features 30 facial muscles animated by brushless micro-motors and managed by a high-precision control system. Paired with an ability to detect their users’ emotions with low latency and bionic skin, their facial expressions are nearly identical to those of humans, reported CGTN. The company claims it’s pioneering the development of realistic humanoid robots designed to revolutionize human-robot interaction. It’s enhancing sophisticated humanoid robot heads that can express emotions, perceive their environment, and interact seamlessly with humans. By combining cutting-edge AI and advanced robotics, AheadForm aims to bring life to machines and transform how humans engage with technology. AI models boost robots’ responsiveness Seamless integration of Large Language Models (LLMs) and Vision-Language Models (VLMs) into the humanoid robots can help them process and interpret complex data from human interactions, enabling the robot to learn and adapt in real-time, achieving human-level understanding and responsiveness. AheadForm uses Brushless Motors that deliver ultra-quiet operation and high responsiveness, specifically designed for precision facial movements in humanoid robots. With its compact size, lightweight design, and energy efficiency, this motor is the ideal choice for next-generation robots that require precise, subtle facial control to create a truly human-like experience. Previously, the company unveiled the Lan Series that features realistic humanoid robots with soft skin and 10 degrees of freedom, offering a lifelike appearance and intuitive movements. This series is designed for cost-efficiency, for applications prioritizing mobility and manipulation.

Owen Gregorian

179,005 次观看 • 10 个月前

A new humanoid robot has been released. EstunCodroid, based in Nanjing, has unveiled its second-generation humanoid robot, Codroid2. Standing 170 cm tall and weighing 70 kg, Codroid2 features a payload capacity of 5 kg per arm and a total of 31 degrees of freedom. Powered by the VLA large language model, it supports multi-robot collaboration and is designed for applications in industrial manufacturing. It can perform physically demanding tasks such as component picking and material handling, as well as precision operations like screw fastening and quality inspection patrols, helping to reduce the burden on human workers. It is worth mentioning that EstunCodroid’s parent company, Estun, is a world-renowned industrial collaborative robot service provider.
2:03

A new humanoid robot has been released. EstunCodroid, based in Nanjing, has unveiled its second-generation humanoid robot, Codroid2. Standing 170 cm tall and weighing 70 kg, Codroid2 features a payload capacity of 5 kg per arm and a total of 31 degrees of freedom. Powered by the VLA large language model, it supports multi-robot collaboration and is designed for applications in industrial manufacturing. It can perform physically demanding tasks such as component picking and material handling, as well as precision operations like screw fastening and quality inspection patrols, helping to reduce the burden on human workers. It is worth mentioning that EstunCodroid’s parent company, Estun, is a world-renowned industrial collaborative robot service provider.

CyberRobo

30,114 次观看 • 1 年前

🦿Xpeng showed a humanoid robot called IRON whose movement looked so human that the team literally cut it open on stage to prove it is a machine. IRON uses a bionic body with a flexible spine, synthetic muscles, and soft skin so joints and torso can twist smoothly like a person. The system has 82 degrees of freedom in total with 22 in each hand for fine finger control. Compute runs on 3 custom AI chips rated at 2,250 TOPS (Tera Operations Per Second), which is far above typical laptop neural accelerators, so it can handle vision and motion planning on the robot. The AI stack focuses on turning camera input directly into body movement without routing through text, which reduces lag and makes the gait look natural. Xpeng staged the cut-open demo at AI Day in Guangzhou this week, addressing rumors that a performer was inside by exposing internal actuators, wiring, and cooling. Company materials also mention a large physical-world model and a multi-brain control setup for dialogue, perception, and locomotion, hinting at a path from stage demos to service work. Production is targeted for 2026, so near-term tasks will be limited, but the hardware shows a serious step toward human-scale manipulation.
0:17

🦿Xpeng showed a humanoid robot called IRON whose movement looked so human that the team literally cut it open on stage to prove it is a machine. IRON uses a bionic body with a flexible spine, synthetic muscles, and soft skin so joints and torso can twist smoothly like a person. The system has 82 degrees of freedom in total with 22 in each hand for fine finger control. Compute runs on 3 custom AI chips rated at 2,250 TOPS (Tera Operations Per Second), which is far above typical laptop neural accelerators, so it can handle vision and motion planning on the robot. The AI stack focuses on turning camera input directly into body movement without routing through text, which reduces lag and makes the gait look natural. Xpeng staged the cut-open demo at AI Day in Guangzhou this week, addressing rumors that a performer was inside by exposing internal actuators, wiring, and cooling. Company materials also mention a large physical-world model and a multi-brain control setup for dialogue, perception, and locomotion, hinting at a path from stage demos to service work. Production is targeted for 2026, so near-term tasks will be limited, but the hardware shows a serious step toward human-scale manipulation.

Rohan Paul

3,802,543 次观看 • 9 个月前

Brain-controlled exoskeletons to train humanoid robots! 🧠 Fourier just presented human tele-operators using brain control interfaces and exoskeletal arms to train humanoid robots on home tasks. The brain control interface is the interesting part. Instead of using a controller or joystick to teleoperate, the operator's movements and intentions are captured more naturally through the exoskeleton and BCI. This means the demonstrations are more fluid, more human-like, and better suited for training robots to perform delicate home tasks. Multiple tele-operators are simultaneously generating training data across multiple robots. This is how you build the dataset needed for eventual full autonomy, without waiting years for it to arrive. This might be the bridge between "robots that work in controlled environments" and "robots that work in homes." Not full autonomy right away, but trusted human intelligence operating through a robot body, getting better with every task completed. ~~ ♻️ Join the weekly robotics newsletter, and never miss any news →
0:56

Brain-controlled exoskeletons to train humanoid robots! 🧠 Fourier just presented human tele-operators using brain control interfaces and exoskeletal arms to train humanoid robots on home tasks. The brain control interface is the interesting part. Instead of using a controller or joystick to teleoperate, the operator's movements and intentions are captured more naturally through the exoskeleton and BCI. This means the demonstrations are more fluid, more human-like, and better suited for training robots to perform delicate home tasks. Multiple tele-operators are simultaneously generating training data across multiple robots. This is how you build the dataset needed for eventual full autonomy, without waiting years for it to arrive. This might be the bridge between "robots that work in controlled environments" and "robots that work in homes." Not full autonomy right away, but trusted human intelligence operating through a robot body, getting better with every task completed. ~~ ♻️ Join the weekly robotics newsletter, and never miss any news →

Lukas Ziegler

20,898 次观看 • 6 个月前

Today at Meta FAIR we’re announcing three new cutting-edge developments in robotics and touch perception — and releasing a collection of artifacts to empower the community to build on this work. Details on all of this new work ➡️ 1️⃣ Meta Sparsh is the first general-purpose encoder for vision-based tactile sensing that works across many tactile sensors and many tasks. Trained on 460K+ tactile images using self-supervised learning. 2️⃣ Meta Digit 360 is a breakthrough artificial fingertip-based tactile sensor, equipped with 18+ sensing features to deliver detailed touch data with human-level precision and touch-sensing capabilities. 3️⃣ Meta Digit Plexus is a standardized platform for robotic sensor connections and interactions. It provides a hardware-software solution to integrate tactile sensors on a single robot hand and enables seamless data collection, control and analysis over a single cable. The potential impact of expanding capabilities and components like these for the open source community ranges from medical research to supply chain, manufacturing and much more. We’re excited to continue this work with the broader community.
2:35

Today at Meta FAIR we’re announcing three new cutting-edge developments in robotics and touch perception — and releasing a collection of artifacts to empower the community to build on this work. Details on all of this new work ➡️ 1️⃣ Meta Sparsh is the first general-purpose encoder for vision-based tactile sensing that works across many tactile sensors and many tasks. Trained on 460K+ tactile images using self-supervised learning. 2️⃣ Meta Digit 360 is a breakthrough artificial fingertip-based tactile sensor, equipped with 18+ sensing features to deliver detailed touch data with human-level precision and touch-sensing capabilities. 3️⃣ Meta Digit Plexus is a standardized platform for robotic sensor connections and interactions. It provides a hardware-software solution to integrate tactile sensors on a single robot hand and enables seamless data collection, control and analysis over a single cable. The potential impact of expanding capabilities and components like these for the open source community ranges from medical research to supply chain, manufacturing and much more. We’re excited to continue this work with the broader community.

AI at Meta

453,343 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:
1:52

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

51,490 次观看 • 1 年前

Brett Adcock, Figure CEO joined our 8 hour(!) live stream where a bunch of us were bird dogging and discussing Figure’s own 8 hour livestream showing a F.03 bot doing a logistics task completely autonomously including shift changes between bots. Here’s my summary of Brett’s remarks. The attached video is just the segment with Brett. We were first introduced to F.03 8 months ago, but Figure has been hard at work on their next version, F.04 which has just completed design lock, so expect to see that new bot sometimes this fall. F.04 was co-designed with the latest Figure AI stack called Helix and was built specifically for data. Brett didn’t explain what that meant, but I suspect it means the bot has many more sensors to enable better training and transfer learning. F.04 will be the biggest leap in performance they’ve had between versions so far which is saying something. Brett is a huge proponent of cross training the bots with many different tasks such that seeming unrelated tasks makes all learned tasks better. He gave an example of the fridge loading training which was topping out at 60% reliability until they trained the same model with kitchen shelving tasks, then they saw the fridge tasks jump to 90% accuracy. As such, they spend almost all their time in pre-training the unified Helix model to ensure they get cross training benefits. Figure will have almost completely localized Figure’s supply chain away from China by next quarter. They build almost everything in-house. Figure does not appear eager to get their bots into the workforce. Brett said they could, today, push thousands of bots into customer hands, and I believe him. But their goal is full general robotics where you can describe a brand new task to a robot, maybe do a one time demonstration, just like you would to a human showing them a new task, and then have the robot do the task. This is the holy grail of AI robotics, and Figure is laser focused on that mission. Brett initially said there was a possibility of achieving it this year, but then guided next couple of years, which I think is much more likely. Personally, I think they’ll need at least a new generation of NVIDIA inference chips to make that leap, and a lot more data gathering, training and hardware development. Brett said their goal with the hardware is “Apple” quality. Ie. Something as well designed and made as any Apple product. While the F.03 hand is clearly performant as shown in the 8 hour livestream, they are building a new hand for the F.04 bot which will be even closer to the full functionality of a human hand. Brett fully believes you need a humanoid hand as close as possible in capability to a human hand, if for no other reason that transfer learning from humans works a lot better when you can exactly mimic what a human does. If the bot can’t do something a human demonstrates, then you’ve just polluted your dataset. By now Figure has built more hands than bot versions (5-6 hands). One of the first hands they tried was a tendon driven hand, and without explaining why, Brett said that was a dead end. Their hands now have all actuators in the hand itself, and are clearly already robust. Brett said he just sat through a 100 page powerpoint design review of the latest hand - that’s how complicated it is. Brett’s other AI company, Hark Labs, has developed a conversational voice model which is installed now in the Figure bots roaming the office. Being able to converse back and forth with a Figure bot is now a thing and will get better over time. All in all, I came away from this segment even more bullish on Figure.
56:47

Brett Adcock, Figure CEO joined our 8 hour(!) live stream where a bunch of us were bird dogging and discussing Figure’s own 8 hour livestream showing a F.03 bot doing a logistics task completely autonomously including shift changes between bots. Here’s my summary of Brett’s remarks. The attached video is just the segment with Brett. We were first introduced to F.03 8 months ago, but Figure has been hard at work on their next version, F.04 which has just completed design lock, so expect to see that new bot sometimes this fall. F.04 was co-designed with the latest Figure AI stack called Helix and was built specifically for data. Brett didn’t explain what that meant, but I suspect it means the bot has many more sensors to enable better training and transfer learning. F.04 will be the biggest leap in performance they’ve had between versions so far which is saying something. Brett is a huge proponent of cross training the bots with many different tasks such that seeming unrelated tasks makes all learned tasks better. He gave an example of the fridge loading training which was topping out at 60% reliability until they trained the same model with kitchen shelving tasks, then they saw the fridge tasks jump to 90% accuracy. As such, they spend almost all their time in pre-training the unified Helix model to ensure they get cross training benefits. Figure will have almost completely localized Figure’s supply chain away from China by next quarter. They build almost everything in-house. Figure does not appear eager to get their bots into the workforce. Brett said they could, today, push thousands of bots into customer hands, and I believe him. But their goal is full general robotics where you can describe a brand new task to a robot, maybe do a one time demonstration, just like you would to a human showing them a new task, and then have the robot do the task. This is the holy grail of AI robotics, and Figure is laser focused on that mission. Brett initially said there was a possibility of achieving it this year, but then guided next couple of years, which I think is much more likely. Personally, I think they’ll need at least a new generation of NVIDIA inference chips to make that leap, and a lot more data gathering, training and hardware development. Brett said their goal with the hardware is “Apple” quality. Ie. Something as well designed and made as any Apple product. While the F.03 hand is clearly performant as shown in the 8 hour livestream, they are building a new hand for the F.04 bot which will be even closer to the full functionality of a human hand. Brett fully believes you need a humanoid hand as close as possible in capability to a human hand, if for no other reason that transfer learning from humans works a lot better when you can exactly mimic what a human does. If the bot can’t do something a human demonstrates, then you’ve just polluted your dataset. By now Figure has built more hands than bot versions (5-6 hands). One of the first hands they tried was a tendon driven hand, and without explaining why, Brett said that was a dead end. Their hands now have all actuators in the hand itself, and are clearly already robust. Brett said he just sat through a 100 page powerpoint design review of the latest hand - that’s how complicated it is. Brett’s other AI company, Hark Labs, has developed a conversational voice model which is installed now in the Figure bots roaming the office. Being able to converse back and forth with a Figure bot is now a thing and will get better over time. All in all, I came away from this segment even more bullish on Figure.

Phil Trubey

33,861 次观看 • 3 个月前

Who can say no to a humanoid robot that can actually feel a hug? 🤖 JQ Industries just built a fabric-based electronic skin for Unitree G1 — covering the torso, hands, and feet. This is not about appearance. It’s about giving robots real tactile sensing and pressure feedback. According to the company, the system includes tactile gloves, upper-body skin, and foot sensors. That means the robot can feel contact through its hands, detect pressure across its body, and use foot feedback to adjust balance. This is the missing layer in most humanoids. Vision alone can’t handle physical interaction. Robots need touch to grip safely, react to humans, and stay stable in real-world environments. JQ says its fiber sensors can detect forces as low as 0.01N, handle up to 3500kPa, and bend below 0.1mm radius. The system can also integrate with Isaac Sim, making tactile data usable for training and deployment. Unitree G1 is already built for manipulation and control — this adds the sensing layer it lacked. JQ says it’s now working with multiple humanoid companies, with some systems already shipping at scale. This is what happens when robots stop just seeing the world — and start physically feeling it.
1:56

Who can say no to a humanoid robot that can actually feel a hug? 🤖 JQ Industries just built a fabric-based electronic skin for Unitree G1 — covering the torso, hands, and feet. This is not about appearance. It’s about giving robots real tactile sensing and pressure feedback. According to the company, the system includes tactile gloves, upper-body skin, and foot sensors. That means the robot can feel contact through its hands, detect pressure across its body, and use foot feedback to adjust balance. This is the missing layer in most humanoids. Vision alone can’t handle physical interaction. Robots need touch to grip safely, react to humans, and stay stable in real-world environments. JQ says its fiber sensors can detect forces as low as 0.01N, handle up to 3500kPa, and bend below 0.1mm radius. The system can also integrate with Isaac Sim, making tactile data usable for training and deployment. Unitree G1 is already built for manipulation and control — this adds the sensing layer it lacked. JQ says it’s now working with multiple humanoid companies, with some systems already shipping at scale. This is what happens when robots stop just seeing the world — and start physically feeling it.

RoboHub🤖

10,952 次观看 • 4 个月前

This work makes a humanoid robot do simple parkour moves by looking with a depth camera and choosing the right move on the fly. The big deal is that it turns lots of small human moves into long, real-time robot behavior, without hand-coding every transition or retraining for each new course. A humanoid robot is usually good at steady walking, but it often fails when it has to do fast moves like jumping up, vaulting, or rolling, and then keep going to the next obstacle. The hard part is that you cannot easily collect training data for every possible obstacle shape, distance, and mistake, so robots end up learning a few moves that only work in a narrow setup. This work starts from short clips of real human parkour moves, like stepping over, vaulting, climbing, and rolling. It uses motion matching, which is basically a smart “pick the next clip that fits best right now” search, to stitch those short clips into a long, smooth plan that looks like a human doing a whole course. Then it trains a controller with reinforcement learning (RL), which means the robot learns by trial and error to copy that plan while staying balanced and not falling. After training separate expert controllers for different moves, it compresses them into 1 controller that uses only onboard depth sensing and a simple “go this fast in this direction” command. In real tests on a Unitree G1 humanoid, it can clear multiple obstacles in a row, adapt when obstacles get moved, and climb a wall up to 1.25m.
0:05

This work makes a humanoid robot do simple parkour moves by looking with a depth camera and choosing the right move on the fly. The big deal is that it turns lots of small human moves into long, real-time robot behavior, without hand-coding every transition or retraining for each new course. A humanoid robot is usually good at steady walking, but it often fails when it has to do fast moves like jumping up, vaulting, or rolling, and then keep going to the next obstacle. The hard part is that you cannot easily collect training data for every possible obstacle shape, distance, and mistake, so robots end up learning a few moves that only work in a narrow setup. This work starts from short clips of real human parkour moves, like stepping over, vaulting, climbing, and rolling. It uses motion matching, which is basically a smart “pick the next clip that fits best right now” search, to stitch those short clips into a long, smooth plan that looks like a human doing a whole course. Then it trains a controller with reinforcement learning (RL), which means the robot learns by trial and error to copy that plan while staying balanced and not falling. After training separate expert controllers for different moves, it compresses them into 1 controller that uses only onboard depth sensing and a simple “go this fast in this direction” command. In real tests on a Unitree G1 humanoid, it can clear multiple obstacles in a row, adapt when obstacles get moved, and climb a wall up to 1.25m.

Rohan Paul

37,121 次观看 • 6 个月前

Awesome! This is literally a superhuman hand. 🤖✋ ChangingTek Robotics just dropped a dexterous hand that actually morphs between left and right hand configurations on the fly. It uses cable-driven tech to pull off shapes and reverse bends that human hands can't even dream of doing. The power is real too, with a 50N grip force and 10N at the fingertips while staying precise within 0.1N. It is kind of like a rigid octopus, meaning it is tough enough to crank a wrench or screwdriver but smooth enough to grab a drink. Having this much range of motion in a single hand basically doubles the efficiency of any robotic arm in tight spots. Source: ChangingTek Robotics #Robot #Humanoid #Robotics #AI #EmbodiedAI #PhysicalAI #ChangingTek #DexterousHand #Bionics
0:33

Awesome! This is literally a superhuman hand. 🤖✋ ChangingTek Robotics just dropped a dexterous hand that actually morphs between left and right hand configurations on the fly. It uses cable-driven tech to pull off shapes and reverse bends that human hands can't even dream of doing. The power is real too, with a 50N grip force and 10N at the fingertips while staying precise within 0.1N. It is kind of like a rigid octopus, meaning it is tough enough to crank a wrench or screwdriver but smooth enough to grab a drink. Having this much range of motion in a single hand basically doubles the efficiency of any robotic arm in tight spots. Source: ChangingTek Robotics #Robot #Humanoid #Robotics #AI #EmbodiedAI #PhysicalAI #ChangingTek #DexterousHand #Bionics

RoboHub🤖

13,855 次观看 • 5 个月前

A new member joins the European humanoid robot team. German company Agile Robotics has launched its first industrial humanoid robot, Agile One, featuring intuitive human-robot interaction, dexterous hands (for grasping small screws and touching the screen), and AI-driven operation trained in the real world. It performs tasks such as material collection, handling, picking and placing, loading and unloading machine tools, tool handling, and precision operations. The emergence of humanoid robots by industrial robot companies is a natural progression; they are designed for areas inaccessible to traditional robotic arms and industrial robots, extending operational systems and enhancing business collaboration capabilities. Agile One will be manufactured in Germany in early 2026 and deployed for on-site training at customers to enhance its AI model capabilities. Soon, Europe will enter its second wave of automation driven by intelligent technology.
1:32

A new member joins the European humanoid robot team. German company Agile Robotics has launched its first industrial humanoid robot, Agile One, featuring intuitive human-robot interaction, dexterous hands (for grasping small screws and touching the screen), and AI-driven operation trained in the real world. It performs tasks such as material collection, handling, picking and placing, loading and unloading machine tools, tool handling, and precision operations. The emergence of humanoid robots by industrial robot companies is a natural progression; they are designed for areas inaccessible to traditional robotic arms and industrial robots, extending operational systems and enhancing business collaboration capabilities. Agile One will be manufactured in Germany in early 2026 and deployed for on-site training at customers to enhance its AI model capabilities. Soon, Europe will enter its second wave of automation driven by intelligent technology.

CyberRobo

72,567 次观看 • 9 个月前

NEWS: Humanoid robotics company Figure has released Helix 02, what they claim in their most capable humanoid model yet. "A single neural system that controls the full body directly from pixels, enabling dexterous, long horizon autonomy across an entire room: • Autonomous, long‑horizon loco-manipulation: Helix 02 unloads and reloads a dishwasher across a full-sized kitchen - a four-minute, end-to-end autonomous task that integrates walking, manipulation, and balance with no resets and no human intervention. We believe this is the longest horizon, most complex task completed autonomously by a humanoid robot to date. • All sensors in. All actuators out: Helix 02 connects every onboard sensor - vision, touch, and proprioception - directly to every actuator through a single unified visuomotor neural network. • Human-like whole body control from human data: All results are enabled by System 0, a learned whole‑body controller trained on over 1,000 hours of human motion data and sim‑to‑real reinforcement learning. System 0 replaces 109,504 lines of hand‑engineered C++ with a single neural prior for stable, natural motion. • New classes of dexterity: With Figure 03’s embedded tactile sensing and palm cameras, Helix 02 performs manipulation that was previously out of reach: extracting individual pills, dispensing precise syringe volumes, and singulating small, irregular objects from clutter despite self‑occlusion. Helix 02 is trained on over 1,000 hours of human motion data and integrates vision, touch, and proprioception."
3:25

NEWS: Humanoid robotics company Figure has released Helix 02, what they claim in their most capable humanoid model yet. "A single neural system that controls the full body directly from pixels, enabling dexterous, long horizon autonomy across an entire room: • Autonomous, long‑horizon loco-manipulation: Helix 02 unloads and reloads a dishwasher across a full-sized kitchen - a four-minute, end-to-end autonomous task that integrates walking, manipulation, and balance with no resets and no human intervention. We believe this is the longest horizon, most complex task completed autonomously by a humanoid robot to date. • All sensors in. All actuators out: Helix 02 connects every onboard sensor - vision, touch, and proprioception - directly to every actuator through a single unified visuomotor neural network. • Human-like whole body control from human data: All results are enabled by System 0, a learned whole‑body controller trained on over 1,000 hours of human motion data and sim‑to‑real reinforcement learning. System 0 replaces 109,504 lines of hand‑engineered C++ with a single neural prior for stable, natural motion. • New classes of dexterity: With Figure 03’s embedded tactile sensing and palm cameras, Helix 02 performs manipulation that was previously out of reach: extracting individual pills, dispensing precise syringe volumes, and singulating small, irregular objects from clutter despite self‑occlusion. Helix 02 is trained on over 1,000 hours of human motion data and integrates vision, touch, and proprioception."

Sawyer Merritt

624,770 次观看 • 7 个月前

Holy… is this really not a human? That was my reaction too,I could hardly believe it. This is an ultra-humanlike humanoid robot. 1.73 m tall, 70 kg, with 115 degrees of freedom across the body,36 in the hands alone,and full-body tactile skin. … This is KAI, the first humanoid robot from Shenzhen-based KinetixAI. It’s essentially a 1:1 human replica，except it has no face. I wonder if it could use Aheadform’s M1? that will be interesting. Powered by its KAI World Model and trained on large-scale Engocentric data, it can fold clothes, use tools, handle deliveries and takeout, and assist with childcare,covering a wide range of household tasks. Ok, expectations for Tesla Optimus v3 have been raised once again.
1:26

Holy… is this really not a human? That was my reaction too,I could hardly believe it. This is an ultra-humanlike humanoid robot. 1.73 m tall, 70 kg, with 115 degrees of freedom across the body,36 in the hands alone,and full-body tactile skin. … This is KAI, the first humanoid robot from Shenzhen-based KinetixAI. It’s essentially a 1:1 human replica，except it has no face. I wonder if it could use Aheadform’s M1? that will be interesting. Powered by its KAI World Model and trained on large-scale Engocentric data, it can fold clothes, use tools, handle deliveries and takeout, and assist with childcare,covering a wide range of household tasks. Ok, expectations for Tesla Optimus v3 have been raised once again.

CyberRobo

109,784 次观看 • 4 个月前

Shanghai MATRIX ROBOTICS has released a video of its new generation general-purpose humanoid robot: MATRIX-3. Much more compact than the first generation, without a protruding "rear end," it features an impressive futuristic design, 27-DOF dexterous hand with tendon-driven joints, 3D soft fabric bionic skin (claimed to have tactile sensing), and incorporates a new neural network that allows for zero-shot learning, enabling it to perform tasks in complex environments. It is planned for use in general scenarios such as manufacturing plants, logistics warehouses, and retail supermarkets. However, this is currently just a video, and its actual performance remains to be seen, especially the rapid, sensitive, and free movements of the hands as shown in the video: this would truly be a huge breakthrough.
0:56

Shanghai MATRIX ROBOTICS has released a video of its new generation general-purpose humanoid robot: MATRIX-3. Much more compact than the first generation, without a protruding "rear end," it features an impressive futuristic design, 27-DOF dexterous hand with tendon-driven joints, 3D soft fabric bionic skin (claimed to have tactile sensing), and incorporates a new neural network that allows for zero-shot learning, enabling it to perform tasks in complex environments. It is planned for use in general scenarios such as manufacturing plants, logistics warehouses, and retail supermarkets. However, this is currently just a video, and its actual performance remains to be seen, especially the rapid, sensitive, and free movements of the hands as shown in the video: this would truly be a huge breakthrough.

CyberRobo

192,751 次观看 • 7 个月前