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Proception has launched its first products, ProHand 1.0 and ProGlove 1.0. - 22 total DoF with 18 actuated DoF (including a 2-DoF wrist) - Tendon-driven fingers, 4 joints each - On-board control for 10 ms real-time response - Every actuator reports its full state continuously, fused with a forearm...

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The Humanoid Hub

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190,287 görüntüleme • 1 ay önce •via X (Twitter)

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A stunning piece of engineering!! 1X unveils the new humanoid hand for NEO - 25 degrees of freedom: 22 fully actuated in the fingers and palm, plus 3 at the wrist. - The DoF are distributed anatomically rather than evenly, deliberately biased toward a thumb that genuinely opposes the fingers. - In-house tendon-driven, quasi-direct-drive running low gear ratios of ~5:1 to 15:1 vs the typical 100:1–200:1. - Motors live in the forearm and pull tendons through the wrist. This keeps the hand light and its inertia low while producing high forces. Sensing - All 25 DoF are natively force-controlled and fully backdrivable. Every joint doubles as a force sensor. - Very important, closed-loop proprioception: it always knows its own pose and effort without looking. - Tactile skin across the fingertips and surfaces measuring contact and shear. This helps with adaptive gripping in real time. Safety and durability - IP68 waterproof and food-safe, so it can wash its own hands. - Compliant by construction: the low gear ratios, tendon drive, and low distal inertia let external impacts safely backdrive the fingers. It yields when hit by a hammer or caught in a drawer. - Full finger assemblies validated to millions of cycles. Manufacturing - Deep vertical integration: in-house motors, custom electronics, and tendon systems. - Hundreds built already, with capacity to produce 10,000 hands this year. "An API to the Physical World"
1:47

A stunning piece of engineering!! 1X unveils the new humanoid hand for NEO - 25 degrees of freedom: 22 fully actuated in the fingers and palm, plus 3 at the wrist. - The DoF are distributed anatomically rather than evenly, deliberately biased toward a thumb that genuinely opposes the fingers. - In-house tendon-driven, quasi-direct-drive running low gear ratios of ~5:1 to 15:1 vs the typical 100:1–200:1. - Motors live in the forearm and pull tendons through the wrist. This keeps the hand light and its inertia low while producing high forces. Sensing - All 25 DoF are natively force-controlled and fully backdrivable. Every joint doubles as a force sensor. - Very important, closed-loop proprioception: it always knows its own pose and effort without looking. - Tactile skin across the fingertips and surfaces measuring contact and shear. This helps with adaptive gripping in real time. Safety and durability - IP68 waterproof and food-safe, so it can wash its own hands. - Compliant by construction: the low gear ratios, tendon drive, and low distal inertia let external impacts safely backdrive the fingers. It yields when hit by a hammer or caught in a drawer. - Full finger assemblies validated to millions of cycles. Manufacturing - Deep vertical integration: in-house motors, custom electronics, and tendon systems. - Hundreds built already, with capacity to produce 10,000 hands this year. "An API to the Physical World"

The Humanoid Hub

1,272,501 görüntüleme • 1 ay önce

U.S. based humanoid robotics company 1X has just unveiled their new tendon-driven robot hands with 25 degrees of freedom (DOF). • Made in USA • Tendon Drive Ratio: 5:1–15:1 • Wrist Dexterity: 3 DOF • Backdrivability: Fully backdrivable • Tactile Sensing: Pressure + location + slip • Finger Force: Up to 45 N • Wrist Torque: 17.75 Nm • Position Accuracy: ±0.2 mm • Waterproof Rating: IP68 • Reliability: >2 million cycles "These hands are designed to do something fundamental: remove the hardware ceiling on what humanoid robots can actually do, and make data the only barrier to capabilities. By matching or surpassing human hands across the dimensions that matter, they ensure our AI models are no longer limited by dexterity. NEO can now perform virtually any task a human can do with their hands– with the precision, adaptability, and gentleness required for real-world environments."
1:04

U.S. based humanoid robotics company 1X has just unveiled their new tendon-driven robot hands with 25 degrees of freedom (DOF). • Made in USA • Tendon Drive Ratio: 5:1–15:1 • Wrist Dexterity: 3 DOF • Backdrivability: Fully backdrivable • Tactile Sensing: Pressure + location + slip • Finger Force: Up to 45 N • Wrist Torque: 17.75 Nm • Position Accuracy: ±0.2 mm • Waterproof Rating: IP68 • Reliability: >2 million cycles "These hands are designed to do something fundamental: remove the hardware ceiling on what humanoid robots can actually do, and make data the only barrier to capabilities. By matching or surpassing human hands across the dimensions that matter, they ensure our AI models are no longer limited by dexterity. NEO can now perform virtually any task a human can do with their hands– with the precision, adaptability, and gentleness required for real-world environments."

Sawyer Merritt

743,013 görüntüleme • 1 ay önce

We trained a humanoid with 22-DoF dexterous hands to assemble model cars, operate syringes, sort poker cards, fold/roll shirts, all learned primarily from 20,000+ hours of egocentric human video with no robot in the loop. Humans are the most scalable embodiment on the planet. We discovered a near-perfect log-linear scaling law (R² = 0.998) between human video volume and action prediction loss, and this loss directly predicts real-robot success rate. Humanoid robots will be the end game, because they are the practical form factor with minimal embodiment gap from humans. Call it the Bitter Lesson of robot hardware: the kinematic similarity lets us simply retarget human finger motion onto dexterous robot hand joints. No learned embeddings, no fancy transfer algorithms needed. Relative wrist motion + retargeted 22-DoF finger actions serve as a unified action space that carries through from pre-training to robot execution. Our recipe is called "EgoScale": - Pre-train GR00T N1.5 on 20K hours of human video, mid-train with only 4 hours (!) of robot play data with Sharpa hands. 54% gains over training from scratch across 5 highly dexterous tasks. - Most surprising result: a *single* teleop demo is sufficient to learn a never-before-seen task. Our recipe enables extreme data efficiency. - Although we pre-train in 22-DoF hand joint space, the policy transfers to a Unitree G1 with 7-DoF tri-finger hands. 30%+ gains over training on G1 data alone. The scalable path to robot dexterity was never more robots. It was always us. Deep dives in thread:
1:17

We trained a humanoid with 22-DoF dexterous hands to assemble model cars, operate syringes, sort poker cards, fold/roll shirts, all learned primarily from 20,000+ hours of egocentric human video with no robot in the loop. Humans are the most scalable embodiment on the planet. We discovered a near-perfect log-linear scaling law (R² = 0.998) between human video volume and action prediction loss, and this loss directly predicts real-robot success rate. Humanoid robots will be the end game, because they are the practical form factor with minimal embodiment gap from humans. Call it the Bitter Lesson of robot hardware: the kinematic similarity lets us simply retarget human finger motion onto dexterous robot hand joints. No learned embeddings, no fancy transfer algorithms needed. Relative wrist motion + retargeted 22-DoF finger actions serve as a unified action space that carries through from pre-training to robot execution. Our recipe is called "EgoScale": - Pre-train GR00T N1.5 on 20K hours of human video, mid-train with only 4 hours (!) of robot play data with Sharpa hands. 54% gains over training from scratch across 5 highly dexterous tasks. - Most surprising result: a *single* teleop demo is sufficient to learn a never-before-seen task. Our recipe enables extreme data efficiency. - Although we pre-train in 22-DoF hand joint space, the policy transfers to a Unitree G1 with 7-DoF tri-finger hands. 30%+ gains over training on G1 data alone. The scalable path to robot dexterity was never more robots. It was always us. Deep dives in thread:

Jim Fan

294,395 görüntüleme • 5 ay önce

Impressive on every dimension! Genesis AI has announced GENE-26.5, its first robotic foundation model, aimed at achieving human-level dexterous manipulation: - Single model, shared weights, handles egg cracking, lab pipetting, bimanual Rubik's Cube, smoothie making, and wire harnessing. Most tasks: under 1 hour of task-specific data, 1x real-world speed. - Genesis Hand 1.0: human-size, 20 active DoF, soft-contact skin. Paired glove gives a 1:1:1 mapping (glove, human hand, robot hand). 100x cheaper than teleop, 5x more data-efficient internally. - Data engine pulls from three sources: glove data, egocentric (head-cam) video, and large-scale internet video. The 1:1 hand-to-human match closes the embodiment gap, letting Genesis use video data more effectively than rivals. - Flow matching across vision, tactile, proprioception, and language inputs. Per Genesis, scaling data and compute directly improves zero-shot
3:55

Impressive on every dimension! Genesis AI has announced GENE-26.5, its first robotic foundation model, aimed at achieving human-level dexterous manipulation: - Single model, shared weights, handles egg cracking, lab pipetting, bimanual Rubik's Cube, smoothie making, and wire harnessing. Most tasks: under 1 hour of task-specific data, 1x real-world speed. - Genesis Hand 1.0: human-size, 20 active DoF, soft-contact skin. Paired glove gives a 1:1:1 mapping (glove, human hand, robot hand). 100x cheaper than teleop, 5x more data-efficient internally. - Data engine pulls from three sources: glove data, egocentric (head-cam) video, and large-scale internet video. The 1:1 hand-to-human match closes the embodiment gap, letting Genesis use video data more effectively than rivals. - Flow matching across vision, tactile, proprioception, and language inputs. Per Genesis, scaling data and compute directly improves zero-shot

The Humanoid Hub

95,691 görüntüleme • 3 ay önce

Xynova just launched Flex 2, its second-gen hybrid dexterous hand — and Xiaomi is already on the cap table. 🤖✋ The spec sheet is sharp: 23 DOF, 400g palm, ±0.1mm repeatability, 0.05N force control, 12kg single-hand grasp load, and multimodal sensing for adaptive grasping and slip detection. Xynova is not only building a robotic hand. It is building the manipulation stack around it: micro linear actuators, joint modules, sensing, control, and developer-facing integration. The Xiaomi link is confirmed. Xiaomi Strategic Investment joined Xynova’s angel round and continued adding in the Pre-A round. What is not confirmed: whether Xiaomi’s own robot hand uses Xynova’s technology. That detail still has no public proof. But the direction is clear: Xiaomi is putting money into the component layer that decides whether humanoids can actually handle objects, tools, and daily tasks. This is the part of robotics that rarely looks flashy on stage. But it decides what a robot can really do with its hands.
0:35

Xynova just launched Flex 2, its second-gen hybrid dexterous hand — and Xiaomi is already on the cap table. 🤖✋ The spec sheet is sharp: 23 DOF, 400g palm, ±0.1mm repeatability, 0.05N force control, 12kg single-hand grasp load, and multimodal sensing for adaptive grasping and slip detection. Xynova is not only building a robotic hand. It is building the manipulation stack around it: micro linear actuators, joint modules, sensing, control, and developer-facing integration. The Xiaomi link is confirmed. Xiaomi Strategic Investment joined Xynova’s angel round and continued adding in the Pre-A round. What is not confirmed: whether Xiaomi’s own robot hand uses Xynova’s technology. That detail still has no public proof. But the direction is clear: Xiaomi is putting money into the component layer that decides whether humanoids can actually handle objects, tools, and daily tasks. This is the part of robotics that rarely looks flashy on stage. But it decides what a robot can really do with its hands.

RoboHub🤖

71,176 görüntüleme • 3 ay önce

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 görüntüleme • 7 ay önce

VLAI Robotics Launches High-Dexterity Dual-Arm Robot Starting at ~$5,500 USD VLAI Robotics, utilizing the open-source design of Japan’s OpenArm team, has introduced a high-dexterity, low-cost bimanual robotic system. The product is priced from 39,900 RMB (approximately 5,500 USD), making high-level research tools accessible to institutions and developers. The robot features a human-scale, arm-hand integrated design with up to 16 DOF (8 DOF per arm, including the gripper). It can handle a dual-arm peak payload of 12 kg while maintaining high precision. A key breakthrough is its ability to replicate human upper limb movement trajectories, which enhances data quality for imitation learning and remote operation. VLAI Robotics handled the domestic engineering, manufacturing, and VLA (Vision-Language-Action) algorithm integration, with quality control organized according to the strict standards of the OpenArm R&D framework. The robot is highly adaptable for research, education, and Physical AI training, supporting easy expansion for features like VR teleoperation.
1:43

VLAI Robotics Launches High-Dexterity Dual-Arm Robot Starting at ~$5,500 USD VLAI Robotics, utilizing the open-source design of Japan’s OpenArm team, has introduced a high-dexterity, low-cost bimanual robotic system. The product is priced from 39,900 RMB (approximately 5,500 USD), making high-level research tools accessible to institutions and developers. The robot features a human-scale, arm-hand integrated design with up to 16 DOF (8 DOF per arm, including the gripper). It can handle a dual-arm peak payload of 12 kg while maintaining high precision. A key breakthrough is its ability to replicate human upper limb movement trajectories, which enhances data quality for imitation learning and remote operation. VLAI Robotics handled the domestic engineering, manufacturing, and VLA (Vision-Language-Action) algorithm integration, with quality control organized according to the strict standards of the OpenArm R&D framework. The robot is highly adaptable for research, education, and Physical AI training, supporting easy expansion for features like VR teleoperation.

RoboHub🤖

12,961 görüntüleme • 9 ay önce

🚀 We’re excited to announce LingBot-VA, a new state-of-the-art robot policy model from Robbyant ! LingBot-VA is built on a causal, autoregressive video-action world model for generalist robot control. Highlights: (1) First unified autoregressive video-action world model for robot control (2) Low-latency inference with a new asynchronous execution pipeline (3) SOTA on RoboTwin (92.9%, firstever > 90%) and LIBERO (98.5%) (4) +20% over π0.5 on challenging real-world long-horizon & high-precision tasks
1:51

🚀 We’re excited to announce LingBot-VA, a new state-of-the-art robot policy model from Robbyant ! LingBot-VA is built on a causal, autoregressive video-action world model for generalist robot control. Highlights: (1) First unified autoregressive video-action world model for robot control (2) Low-latency inference with a new asynchronous execution pipeline (3) SOTA on RoboTwin (92.9%, firstever > 90%) and LIBERO (98.5%) (4) +20% over π0.5 on challenging real-world long-horizon & high-precision tasks

Yinghao Xu

46,962 görüntüleme • 6 ay önce

Xpeng unveiled its next-generation IRON humanoid robot at the 2025 Xpeng Tech Day. This version emphasizes a "born from within" bionic design philosophy, featuring a human-like spine structure, full flexible skin, and customizable physique, including the option for male and female forms. CEO He Xiaopeng confirmed this is the final pre-research version, with the mass-production model standing no taller than 170cm. IRON’s technical specs are aggressive: 🦾 Hardware: 82 total Degrees of Freedom (DoF), far above the average. Its hand boasts 22 DoF with industry-smallest harmonic joints for 1:1 human hand scale, enabling delicate tasks (grabbing eggs, unscrewing caps). 🧠 Intelligence: Runs on three Turing AI chips with 2,250 TOPS of effective computing power, currently the highest in humanoids. It debuts Xpeng's first-gen Physical World Large Model (VLT + VLA + VLM) for high-level dialogue and control. 🔋 Solid-State Power: IRON is the first to use full solid-state batteries, boosting power by 30% and reducing weight by 30%. Xpeng aims for this safety-critical sector to drive SS battery mass production. 🚀 Commercialization Plan: Xpeng will prioritize commercial scenarios like guidance, sales assistance, and inspection (jointly developing complex applications with partners like Baosteel Group). CEO He Xiaopeng plans aggressive scaled mass production of advanced humanoids by the end of 2026. The robot team is over 1,000 people.
3:46

Xpeng unveiled its next-generation IRON humanoid robot at the 2025 Xpeng Tech Day. This version emphasizes a "born from within" bionic design philosophy, featuring a human-like spine structure, full flexible skin, and customizable physique, including the option for male and female forms. CEO He Xiaopeng confirmed this is the final pre-research version, with the mass-production model standing no taller than 170cm. IRON’s technical specs are aggressive: 🦾 Hardware: 82 total Degrees of Freedom (DoF), far above the average. Its hand boasts 22 DoF with industry-smallest harmonic joints for 1:1 human hand scale, enabling delicate tasks (grabbing eggs, unscrewing caps). 🧠 Intelligence: Runs on three Turing AI chips with 2,250 TOPS of effective computing power, currently the highest in humanoids. It debuts Xpeng's first-gen Physical World Large Model (VLT + VLA + VLM) for high-level dialogue and control. 🔋 Solid-State Power: IRON is the first to use full solid-state batteries, boosting power by 30% and reducing weight by 30%. Xpeng aims for this safety-critical sector to drive SS battery mass production. 🚀 Commercialization Plan: Xpeng will prioritize commercial scenarios like guidance, sales assistance, and inspection (jointly developing complex applications with partners like Baosteel Group). CEO He Xiaopeng plans aggressive scaled mass production of advanced humanoids by the end of 2026. The robot team is over 1,000 people.

RoboHub🤖

23,275 görüntüleme • 9 ay önce

Feeling what a robot feels is becoming real! 🫰 Fluid Reality just ran its first full end-to-end touch teleoperation system, and the demo shows why high-resolution haptics might be the missing piece in robot control. A 22 mm fingertip display with 32 independently actuated “bubbles” was mapped directly to tactile sensors on a robot hand. 🫧 Three fingers streamed real-time touch data robot → human, giving the operator actual contact feedback instead of waving their hands blind, like most teleop systems today. It’s still early, but this is a real step toward dexterous ops and high-quality data for training Physical AI systems. Companies involved: Samsung Electronics, Alt-Bionics, Inc. (the robot hand), MANUS™ (hand tracking), and Sensible Robotics (fingertip sensors) Touch isn’t a nice-to-have in robotics. It’s the difference between manipulation that works in the real world P.S. Guess how many touch receptors we humans, have in our hand! :) ~~ ♻ Join the weekly robotics newsletter, and never miss any news →
1:23

Feeling what a robot feels is becoming real! 🫰 Fluid Reality just ran its first full end-to-end touch teleoperation system, and the demo shows why high-resolution haptics might be the missing piece in robot control. A 22 mm fingertip display with 32 independently actuated “bubbles” was mapped directly to tactile sensors on a robot hand. 🫧 Three fingers streamed real-time touch data robot → human, giving the operator actual contact feedback instead of waving their hands blind, like most teleop systems today. It’s still early, but this is a real step toward dexterous ops and high-quality data for training Physical AI systems. Companies involved: Samsung Electronics, Alt-Bionics, Inc. (the robot hand), MANUS™ (hand tracking), and Sensible Robotics (fingertip sensors) Touch isn’t a nice-to-have in robotics. It’s the difference between manipulation that works in the real world P.S. Guess how many touch receptors we humans, have in our hand! :) ~~ ♻ Join the weekly robotics newsletter, and never miss any news →

Lukas Ziegler

46,927 görüntüleme • 8 ay önce

Listen, speak, handle interruptions, and call tools in one live conversation. 🎙️ Introducing NVIDIA-NemotronLabs-VoiceChat-11B, NVIDIA’s end-to-end full-duplex model for real-time voice agents. 🤖 🏆 It ranks #2 among open full-duplex models on both VoiceBench and Full-Duplex-Bench 1.0. ⚡ Natural turn-taking responds in ~448 ms, while barge-in lets users interrupt the model with ~480 ms latency. 🛠️ The first open full-duplex model with live tool calling. One unified system handles speech understanding, generation, transcription, and tool execution while keeping the conversation flowing. 🧠 Built with a Fast Conformer, Nemotron Nano v2, and a TTS decoder, trained on ~550K hours of real and synthetic speech. 📜 Research use only. OpenMDW 1.1.
1:24

Listen, speak, handle interruptions, and call tools in one live conversation. 🎙️ Introducing NVIDIA-NemotronLabs-VoiceChat-11B, NVIDIA’s end-to-end full-duplex model for real-time voice agents. 🤖 🏆 It ranks #2 among open full-duplex models on both VoiceBench and Full-Duplex-Bench 1.0. ⚡ Natural turn-taking responds in ~448 ms, while barge-in lets users interrupt the model with ~480 ms latency. 🛠️ The first open full-duplex model with live tool calling. One unified system handles speech understanding, generation, transcription, and tool execution while keeping the conversation flowing. 🧠 Built with a Fast Conformer, Nemotron Nano v2, and a TTS decoder, trained on ~550K hours of real and synthetic speech. 📜 Research use only. OpenMDW 1.1.

ModelScope

21,832 görüntüleme • 7 gün önce

China unveils humanoid robot worker with brain that runs 275 trillion ops/sec | Jijo Malayil, Interesting Engineering In tests, SUYUAN used vision and joint control to sort and move crates of various sizes, greatly improving warehouse productivity. Chinese manufacturing firm Shanghai Electric has unveiled its first self-developed industrial humanoid robot, “SUYUAN,” marking a major milestone in its robotics journey. Debuting at the World Artificial Intelligence Conference (WAIC 2025) on July 26 in Shanghai, SUYUAN boasts 38 degrees of freedom and 275 TOPS of on-device computing power, enabling precise operations and fluid movements. According to the firm, designed for diverse industrial use, the robot showcases Shanghai Electric’s end-to-end capabilities—from core tech to integrated solutions—and reinforces its commitment to next-gen industrial automation through a full industry chain strategy. At WAIC 2025, Shanghai Electric also unveiled a new joint venture with Johnson Electric for next-gen humanoid robotics and showcased its “LINGKE” dual-arm robot. Recently, Hangzhou-based Unitree Robotics launched the R1 humanoid with 26 joints for $5,900, showcasing athletic feats like cartwheels, running, and quick recovery. Smart factory assistant Shanghai Electric claims SUYUAN, equipped with 38 degrees of freedom (DoF) and a powerful 275 TOPS on-device computing processor, delivers fluid, human-like movements and high-precision operations across various industrial scenarios. Its advanced articulation and real-time processing capabilities make it highly adaptable, enabling smooth execution of complex tasks in dynamic work environments. SUYUAN, who weighs 110 pounds (50 kilograms) and is 5 feet 6 inches (167 cm) tall, was designed to have human-like proportions. Its 38-DoF articulation offers dexterity, allowing for both wide-range motion and sensitive manipulation. With a single arm, the robot can lift objects up to 4.4 pounds (2 kilograms) in weight and carry a total payload of up to 22 pounds (10 kilograms). With a walking pace of 3.1 miles per hour (5 km/h), SUYUAN is ideal for environments including assembly lines, warehousing, and logistics, according to a statement. To navigate complex industrial settings, SUYUAN combines LiDAR and binocular vision for self-guided mobility. Its 275-TOPS AI processor enables rapid data analysis and integration with large language models, allowing it to understand tasks in natural language and handle objects adaptively, reports Fox 44 News. In pilot demonstrations, the robot successfully identified, picked, and relocated crates of varying sizes using advanced computer vision and coordinated joint control—delivering measurable gains in warehouse efficiency. The company claims that SUYUAN’s launch represents a major turning point in Shanghai Electric’s foray into humanoid robotics and strengthens its vertically integrated approach to industrial automation solutions. Intelligent task handling Shanghai Electric also demonstrated its most recent developments in intelligent manufacturing at WAIC 2025, introducing a new joint venture with Johnson Electric centered on next-generation humanoid robotics and showcasing the “LINGKE” dual-arm robot. With its high-precision operations, adaptive teamwork, and closed-loop data capabilities, the LINGKE robot demonstrated live talents in handling complicated production jobs. LINGKE is made to do more than just replace human labor; it uses compliant force control and bimanual coordination to relieve workers of high-intensity, repetitive jobs. According to the company, the robot enhances operational efficiency by up to five times. Its core strength lies in a Data-Model-Deployment closed-loop system that starts with operational data, followed by data cleansing, model training, live deployment, and feedback-driven optimization—enabling autonomous learning and workflow improvement. Also at the event, Shanghai Electric and Johnson Electric introduced advanced hardware modules for humanoid robots, including rotary joints, linear joints, and dexterous finger joints. These components are designed to support smooth, precise, and quiet motion performance across robotics systems, reports Stock Titan. The joint venture announced two strategic agreements: a first-unit supply deal with the National and Local Co-Built Humanoid Robotics Innovation Center (Qinglong Project) and a cooperation memorandum with Fourier Robotics. Read more:
0:58

China unveils humanoid robot worker with brain that runs 275 trillion ops/sec | Jijo Malayil, Interesting Engineering In tests, SUYUAN used vision and joint control to sort and move crates of various sizes, greatly improving warehouse productivity. Chinese manufacturing firm Shanghai Electric has unveiled its first self-developed industrial humanoid robot, “SUYUAN,” marking a major milestone in its robotics journey. Debuting at the World Artificial Intelligence Conference (WAIC 2025) on July 26 in Shanghai, SUYUAN boasts 38 degrees of freedom and 275 TOPS of on-device computing power, enabling precise operations and fluid movements. According to the firm, designed for diverse industrial use, the robot showcases Shanghai Electric’s end-to-end capabilities—from core tech to integrated solutions—and reinforces its commitment to next-gen industrial automation through a full industry chain strategy. At WAIC 2025, Shanghai Electric also unveiled a new joint venture with Johnson Electric for next-gen humanoid robotics and showcased its “LINGKE” dual-arm robot. Recently, Hangzhou-based Unitree Robotics launched the R1 humanoid with 26 joints for $5,900, showcasing athletic feats like cartwheels, running, and quick recovery. Smart factory assistant Shanghai Electric claims SUYUAN, equipped with 38 degrees of freedom (DoF) and a powerful 275 TOPS on-device computing processor, delivers fluid, human-like movements and high-precision operations across various industrial scenarios. Its advanced articulation and real-time processing capabilities make it highly adaptable, enabling smooth execution of complex tasks in dynamic work environments. SUYUAN, who weighs 110 pounds (50 kilograms) and is 5 feet 6 inches (167 cm) tall, was designed to have human-like proportions. Its 38-DoF articulation offers dexterity, allowing for both wide-range motion and sensitive manipulation. With a single arm, the robot can lift objects up to 4.4 pounds (2 kilograms) in weight and carry a total payload of up to 22 pounds (10 kilograms). With a walking pace of 3.1 miles per hour (5 km/h), SUYUAN is ideal for environments including assembly lines, warehousing, and logistics, according to a statement. To navigate complex industrial settings, SUYUAN combines LiDAR and binocular vision for self-guided mobility. Its 275-TOPS AI processor enables rapid data analysis and integration with large language models, allowing it to understand tasks in natural language and handle objects adaptively, reports Fox 44 News. In pilot demonstrations, the robot successfully identified, picked, and relocated crates of varying sizes using advanced computer vision and coordinated joint control—delivering measurable gains in warehouse efficiency. The company claims that SUYUAN’s launch represents a major turning point in Shanghai Electric’s foray into humanoid robotics and strengthens its vertically integrated approach to industrial automation solutions. Intelligent task handling Shanghai Electric also demonstrated its most recent developments in intelligent manufacturing at WAIC 2025, introducing a new joint venture with Johnson Electric centered on next-generation humanoid robotics and showcasing the “LINGKE” dual-arm robot. With its high-precision operations, adaptive teamwork, and closed-loop data capabilities, the LINGKE robot demonstrated live talents in handling complicated production jobs. LINGKE is made to do more than just replace human labor; it uses compliant force control and bimanual coordination to relieve workers of high-intensity, repetitive jobs. According to the company, the robot enhances operational efficiency by up to five times. Its core strength lies in a Data-Model-Deployment closed-loop system that starts with operational data, followed by data cleansing, model training, live deployment, and feedback-driven optimization—enabling autonomous learning and workflow improvement. Also at the event, Shanghai Electric and Johnson Electric introduced advanced hardware modules for humanoid robots, including rotary joints, linear joints, and dexterous finger joints. These components are designed to support smooth, precise, and quiet motion performance across robotics systems, reports Stock Titan. The joint venture announced two strategic agreements: a first-unit supply deal with the National and Local Co-Built Humanoid Robotics Innovation Center (Qinglong Project) and a cooperation memorandum with Fourier Robotics. Read more:

Owen Gregorian

51,638 görüntüleme • 1 yıl önce

⚡SHARPA LEAVES THE LAB, HEADS TO DAIRY QUEEN Sharpa is taking its 22-DoF Wave hand beyond demos with Project Edison, preparing its North robot for a real Dairy Queen deployment in Shanghai. Humanoid Scott got an early look at the project. A few things that really stood out from our conversation: > Sharpa is building the full stack around the hand, including the robot arms, mobile base and AI > North has to work in the existing kitchen, with no redesign of the workspace around the robot > Scott Walter says making a Blizzard involves roughly 50–60 steps through an existing human workflow > The preview footage is teleoperated and sped up. Sharpa expects the released system to be fully autonomous But the bigger story here is Sharpa taking dexterous robot hands from impressive demos to complete systems capable of useful commercial work. And Sharpa founder David Li has offered to join us on Over The Horizon to take us deeper inside Project Edison. Great discussion with Humanoid Scott and Mehrdad Farimani. Looking forward to hopefully having Sharpa and David Li join us for a deeper dive into their work! ⚡Full episode linked below in the thread!👇🏽
3:28

⚡SHARPA LEAVES THE LAB, HEADS TO DAIRY QUEEN Sharpa is taking its 22-DoF Wave hand beyond demos with Project Edison, preparing its North robot for a real Dairy Queen deployment in Shanghai. Humanoid Scott got an early look at the project. A few things that really stood out from our conversation: > Sharpa is building the full stack around the hand, including the robot arms, mobile base and AI > North has to work in the existing kitchen, with no redesign of the workspace around the robot > Scott Walter says making a Blizzard involves roughly 50–60 steps through an existing human workflow > The preview footage is teleoperated and sped up. Sharpa expects the released system to be fully autonomous But the bigger story here is Sharpa taking dexterous robot hands from impressive demos to complete systems capable of useful commercial work. And Sharpa founder David Li has offered to join us on Over The Horizon to take us deeper inside Project Edison. Great discussion with Humanoid Scott and Mehrdad Farimani. Looking forward to hopefully having Sharpa and David Li join us for a deeper dive into their work! ⚡Full episode linked below in the thread!👇🏽

Royden D'Souza

369,693 görüntüleme • 18 gün önce

Reporting from CES 2026 LG Electronics has unveiled LG CLOiD, an AI-powered home robot, advancing its “Zero Labor Home” vision to automate chores. CLOiD features: • Wheeled base for safe navigation • Tilting torso • Two 7-DoF arms with 5-fingered hands for precise manipulation • Head as mobile AI hub equipped with a chipset (its brain), display, speakers, cameras, sensors, and voice-based generative AI for communication, learning user patterns, and appliance control Powered by LG’s Physical AI (VLM for understanding + VLA for actions), trained on tens of thousands of hours of household task data. It performs tasks like breakfast prep, laundry (loading/folding), dishwasher unloading, and more. LG also launched AXIUM actuators lineup for efficient robotics solutions. Vision for the future: AI-driven homes freeing time for meaningful activities.
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Reporting from CES 2026 LG Electronics has unveiled LG CLOiD, an AI-powered home robot, advancing its “Zero Labor Home” vision to automate chores. CLOiD features: • Wheeled base for safe navigation • Tilting torso • Two 7-DoF arms with 5-fingered hands for precise manipulation • Head as mobile AI hub equipped with a chipset (its brain), display, speakers, cameras, sensors, and voice-based generative AI for communication, learning user patterns, and appliance control Powered by LG’s Physical AI (VLM for understanding + VLA for actions), trained on tens of thousands of hours of household task data. It performs tasks like breakfast prep, laundry (loading/folding), dishwasher unloading, and more. LG also launched AXIUM actuators lineup for efficient robotics solutions. Vision for the future: AI-driven homes freeing time for meaningful activities.

The Humanoid Hub

82,570 görüntüleme • 7 ay önce

Sharpa Robotics officially launched its dexterous hand, the SharpaWave, on October 16, moving it into mass production. The hand, which impressed many at ICRA 2025, is built around what the company calls a "Dynamic Tactile Array" (DTA) for high-fidelity sensing. Key specs from the official brochure are noteworthy: • Human-like design: 22 degrees of freedom in a 1:1 human-sized form factor. • Advanced sensing: The DTA features >1000 tactile pixels per fingertip, 20 N of fingertip strength with a movement speed of >4 Hz across all gestures. With out-of-the-box support for ROS and MuJoCo simulation, Sharpa is making a clear play for the robotics R&D community.
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Sharpa Robotics officially launched its dexterous hand, the SharpaWave, on October 16, moving it into mass production. The hand, which impressed many at ICRA 2025, is built around what the company calls a "Dynamic Tactile Array" (DTA) for high-fidelity sensing. Key specs from the official brochure are noteworthy: • Human-like design: 22 degrees of freedom in a 1:1 human-sized form factor. • Advanced sensing: The DTA features >1000 tactile pixels per fingertip, 20 N of fingertip strength with a movement speed of >4 Hz across all gestures. With out-of-the-box support for ROS and MuJoCo simulation, Sharpa is making a clear play for the robotics R&D community.

Humanoids daily

66,083 görüntüleme • 9 ay önce

AGIBOT has unveiled AGILE (AgiBot Generative Intelligent Locomotion Engine), a perception-control foundation model for whole-body humanoid locomotion. - It fuses visual perception, balance, and motion planning end-to-end, replacing the traditional split between "seeing" and "moving." - The robot reads terrain and obstacles in real time and adjusts its gait with no preset trajectories. - It runs on local compute with millisecond-level response and works across AGIBOT's lineup (A1/A2/A3, X2). AGILE is the locomotion "cerebellum" that complements AGIBOT's Genie Operator "brain."
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AGIBOT has unveiled AGILE (AgiBot Generative Intelligent Locomotion Engine), a perception-control foundation model for whole-body humanoid locomotion. - It fuses visual perception, balance, and motion planning end-to-end, replacing the traditional split between "seeing" and "moving." - The robot reads terrain and obstacles in real time and adjusts its gait with no preset trajectories. - It runs on local compute with millisecond-level response and works across AGIBOT's lineup (A1/A2/A3, X2). AGILE is the locomotion "cerebellum" that complements AGIBOT's Genie Operator "brain."

The Humanoid Hub

14,020 görüntüleme • 2 ay önce

AgiBot’s new generation of industrial-grade interactive embodied robot, AgiBot G2, has officially launched! The G2 has already secured orders worth hundreds of millions of RMB, including two separate contracts each exceeding 100 million RMB, and has begun its first commercial deliveries. The AgiBot G2 is built to industrial standards, featuring high-performance joints, precision torque sensors, and an advanced spatial perception system. It supports rapid learning and deployment, offers strong multimodal voice interaction, and is designed for general use in industrial, logistics, and guidance scenarios. Inheriting the successful "Collect-Train-Deploy" model of its predecessor, the G1, the G2 brings significant upgrades, including a high-performance AI computing platform and actuators that enable omnidirectional obstacle avoidance and high-precision force-control tasks. Its 3-DOF waist allows for human-like bending and lateral body movement. A key feature is the G2's globally first-of-its-kind cross-shaped wrist force-control arm, which uses precision joint torque sensors and joint impedance control to delicately perceive external forces and respond smoothly. For continuous operation, the G2 supports autonomous charging and features a dual-battery hot-swapping system, meeting the 24-hour cycle demands of factory production lines. During the launch event, AgiBot demonstrated the G2’s ultra-low latency remote operation (teleoperation) capabilities. Operators successfully demonstrated precision shots (like hitting a floating balloon in Shanghai while operating from Beijing), showcasing the robot's high accuracy and low latency in both line-of-sight and beyond-line-of-sight scenarios. The G2 is already being deployed across four key real-world scenarios: In automotive parts production, it assists humans with tasks like safety belt lock core pressing and material handling. In precision operations, it used reinforcement learning to master delicate tasks like inserting memory sticks in just one hour. In logistics, the G2, enhanced by AgiBot's OmniHand dexterous hand, efficiently handles various package types for sorting and loading. Its strong mobility allows it to adapt to over 95% of factory floors. AgiBot is also commencing the first batch of commercial deliveries under an over 100 million RMB procurement contract with Joyson Electronic, formally landing the G2 in the automotive parts manufacturing sector.
2:28

AgiBot’s new generation of industrial-grade interactive embodied robot, AgiBot G2, has officially launched! The G2 has already secured orders worth hundreds of millions of RMB, including two separate contracts each exceeding 100 million RMB, and has begun its first commercial deliveries. The AgiBot G2 is built to industrial standards, featuring high-performance joints, precision torque sensors, and an advanced spatial perception system. It supports rapid learning and deployment, offers strong multimodal voice interaction, and is designed for general use in industrial, logistics, and guidance scenarios. Inheriting the successful "Collect-Train-Deploy" model of its predecessor, the G1, the G2 brings significant upgrades, including a high-performance AI computing platform and actuators that enable omnidirectional obstacle avoidance and high-precision force-control tasks. Its 3-DOF waist allows for human-like bending and lateral body movement. A key feature is the G2's globally first-of-its-kind cross-shaped wrist force-control arm, which uses precision joint torque sensors and joint impedance control to delicately perceive external forces and respond smoothly. For continuous operation, the G2 supports autonomous charging and features a dual-battery hot-swapping system, meeting the 24-hour cycle demands of factory production lines. During the launch event, AgiBot demonstrated the G2’s ultra-low latency remote operation (teleoperation) capabilities. Operators successfully demonstrated precision shots (like hitting a floating balloon in Shanghai while operating from Beijing), showcasing the robot's high accuracy and low latency in both line-of-sight and beyond-line-of-sight scenarios. The G2 is already being deployed across four key real-world scenarios: In automotive parts production, it assists humans with tasks like safety belt lock core pressing and material handling. In precision operations, it used reinforcement learning to master delicate tasks like inserting memory sticks in just one hour. In logistics, the G2, enhanced by AgiBot's OmniHand dexterous hand, efficiently handles various package types for sorting and loading. Its strong mobility allows it to adapt to over 95% of factory floors. AgiBot is also commencing the first batch of commercial deliveries under an over 100 million RMB procurement contract with Joyson Electronic, formally landing the G2 in the automotive parts manufacturing sector.

RoboHub🤖

33,831 görüntüleme • 9 ay önce

Robotics has a data scarcity problem - you simply can't scrape robot control data from webpages. Introducing GR00T-Mimic and GR00T-Gen: using both Graphics 1.0 & Graphics 2.0 to multiply your robot datasets by 1,000,000x. We trade compute for synthetic data, so we are not capped by the fundamental physical limit of 24 hrs/robot/day. Robotics is right in the thick of Moravec's paradox: things that are easy for humans turn out to be incredibly hard for machines. We are crushing the Moravec's paradox, one token at a time. > Graphics 1.0: Isaac simulators with manually written, GPU-accelerated physics and rendering equations. > Graphics 2.0: big neural nets (Cosmos) that repaint the pixels from sim textures to real, given an open-ended prompt. Robot data multiplier workflow: 1. GR00T-Teleop: use XR device like Apple Vision Pro to map human finger poses to humanoid hands. 2. GR00T-Mimic: given a human-collected task demonstration, we augment the actions in Isaac and filter out ones that fail the task. 3. GR00T-Gen: apply Graphics 1.0 and then Graphics 2.0 to produce tons of visual variations. Join us to build Physical AI together! Job application links in thread:
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Robotics has a data scarcity problem - you simply can't scrape robot control data from webpages. Introducing GR00T-Mimic and GR00T-Gen: using both Graphics 1.0 & Graphics 2.0 to multiply your robot datasets by 1,000,000x. We trade compute for synthetic data, so we are not capped by the fundamental physical limit of 24 hrs/robot/day. Robotics is right in the thick of Moravec's paradox: things that are easy for humans turn out to be incredibly hard for machines. We are crushing the Moravec's paradox, one token at a time. > Graphics 1.0: Isaac simulators with manually written, GPU-accelerated physics and rendering equations. > Graphics 2.0: big neural nets (Cosmos) that repaint the pixels from sim textures to real, given an open-ended prompt. Robot data multiplier workflow: 1. GR00T-Teleop: use XR device like Apple Vision Pro to map human finger poses to humanoid hands. 2. GR00T-Mimic: given a human-collected task demonstration, we augment the actions in Isaac and filter out ones that fail the task. 3. GR00T-Gen: apply Graphics 1.0 and then Graphics 2.0 to produce tons of visual variations. Join us to build Physical AI together! Job application links in thread:

Jim Fan

163,670 görüntüleme • 1 yıl önce

1/🧠Humans are the best robot data source — but video alone misses one thing: force. 2/🙁Tactile gloves capture force — but they're costly and block the real touch manipulation depends on. 3/💪Maybe the future of touch lives on your wrist: surface EMG reads the muscles that cause force — tactile sensing without ever touching a tactile sensor. 4/🔥Want a fully open-source framework — hardware + software — to train your own force-aware learn-from-human-data robot policy? 🚀We introduce ForceBand: Learning Forceful Manipulation with sEMG -- bring force into human videos with sEMG, for force-aware manipulation ⬇️ ✦ Zero-Shot Human-to-Robot Transfer ✦ Force Beyond Vision ✦ Free-Hand Force Sensing ✦ Collect by Anyone, Anytime, Anywhere ✦ Deploy on Any Robot, Any Camera, Any Environment ✦ Open-Source & Low-Cost & Easy-to-Implement Let's squeeze every bit of signal out of human data, and let robots feel the force! 🌐 Website: 📄 Paper: 💻 Code: 🎥 Video: 🧵 1/n
1:48

1/🧠Humans are the best robot data source — but video alone misses one thing: force. 2/🙁Tactile gloves capture force — but they're costly and block the real touch manipulation depends on. 3/💪Maybe the future of touch lives on your wrist: surface EMG reads the muscles that cause force — tactile sensing without ever touching a tactile sensor. 4/🔥Want a fully open-source framework — hardware + software — to train your own force-aware learn-from-human-data robot policy? 🚀We introduce ForceBand: Learning Forceful Manipulation with sEMG -- bring force into human videos with sEMG, for force-aware manipulation ⬇️ ✦ Zero-Shot Human-to-Robot Transfer ✦ Force Beyond Vision ✦ Free-Hand Force Sensing ✦ Collect by Anyone, Anytime, Anywhere ✦ Deploy on Any Robot, Any Camera, Any Environment ✦ Open-Source & Low-Cost & Easy-to-Implement Let's squeeze every bit of signal out of human data, and let robots feel the force! 🌐 Website: 📄 Paper: 💻 Code: 🎥 Video: 🧵 1/n

Zhi (Leo) Wang

50,541 görüntüleme • 1 ay önce

That's sick! 🤯 Genesis AI simulates robots playing yo-yo! 🪀 Genesis AI just open-sourced Genesis World 1.0, and it might be one of the most important infrastructure releases in robotics this year. Robotics is still bottlenecked by the 1× speed of the physical world. Every model needs to be tested on real hardware, slowly, expensively, with limited coverage. Genesis World 1.0 from Genesis AI flips that equation: One hour in reality becomes 100 days in simulation. That turns a wall-clock bottleneck into a compute problem. And compute problems are solvable. The technical stack they rebuilt from scratch is serious: → GPU-accelerated cross-platform compiler via Quadrants, 10x faster launch time and up to 4.6x runtime vs the initial Genesis release → Penetration-free multi-physics contact solvers, the thing that makes simulation actually trustworthy → Unified rigid AND deformable physics in a single engine → Nyx, a high-performance path-traced rendering engine purpose-built for physical AI The sim-to-real gap has historically been the graveyard of robotics research. Policies that work beautifully in simulation fall apart on real hardware. Genesis World 1.0 is a direct attack on that problem. And it's fully open-source. The companies that master simulation infrastructure will train better robots faster than anyone else. Find it here: Genesis World 1.0: Quadrants: Nyx: Theophile Gervet, Zhou Xian congrats! 👏🏼 ~~ ♻️ Join the weekly robotics newsletter, and never miss any news →
0:46

That's sick! 🤯 Genesis AI simulates robots playing yo-yo! 🪀 Genesis AI just open-sourced Genesis World 1.0, and it might be one of the most important infrastructure releases in robotics this year. Robotics is still bottlenecked by the 1× speed of the physical world. Every model needs to be tested on real hardware, slowly, expensively, with limited coverage. Genesis World 1.0 from Genesis AI flips that equation: One hour in reality becomes 100 days in simulation. That turns a wall-clock bottleneck into a compute problem. And compute problems are solvable. The technical stack they rebuilt from scratch is serious: → GPU-accelerated cross-platform compiler via Quadrants, 10x faster launch time and up to 4.6x runtime vs the initial Genesis release → Penetration-free multi-physics contact solvers, the thing that makes simulation actually trustworthy → Unified rigid AND deformable physics in a single engine → Nyx, a high-performance path-traced rendering engine purpose-built for physical AI The sim-to-real gap has historically been the graveyard of robotics research. Policies that work beautifully in simulation fall apart on real hardware. Genesis World 1.0 is a direct attack on that problem. And it's fully open-source. The companies that master simulation infrastructure will train better robots faster than anyone else. Find it here: Genesis World 1.0: Quadrants: Nyx: Theophile Gervet, Zhou Xian congrats! 👏🏼 ~~ ♻️ Join the weekly robotics newsletter, and never miss any news →

Lukas Ziegler

56,807 görüntüleme • 2 ay önce