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📹 WATCH: UNITREE G1 PERFORMING HOUSEHOLD TASKS WITH IMPRESSIVE PRECISION Unitree's G1 humanoid robot was shown recently washing dishes, carrying water, and sorting laundry, perfecting day-to-day chores using a full-body teleoperation system.

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21,987 views • 2 months ago •via X (Twitter)

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Researchers have developed Humanoid-GPT, a new AI system that helps humanoid robots perform complex movements and tasks. Tested on the Unitree G1 robot, it enables real-time whole-body control and can perform new actions without special training. During demonstrations, the robot successfully carried out a variety of movements and tasks, showing strong potential for real-world applications.

Researchers have developed Humanoid-GPT, a new AI system that helps humanoid robots perform complex movements and tasks. Tested on the Unitree G1 robot, it enables real-time whole-body control and can perform new actions without special training. During demonstrations, the robot successfully carried out a variety of movements and tasks, showing strong potential for real-world applications.

Space and Technology

22,052 views • 1 month ago

Unitree Humanoid Robots Updated With Open-Source Full-Body Motion Dataset 🤗 We’ve adapted motion capture data for Unitree H1, H1-2, and G1 humanoid robots, using numerical optimization methods to make their movement trajectories more natural. Open-Source： #AI #OpenSourceDataset #Unitree #EmbodiedAI #Humanoid #DataCollection #AGI #Dance

Unitree Humanoid Robots Updated With Open-Source Full-Body Motion Dataset 🤗 We’ve adapted motion capture data for Unitree H1, H1-2, and G1 humanoid robots, using numerical optimization methods to make their movement trajectories more natural. Open-Source： #AI #OpenSourceDataset #Unitree #EmbodiedAI #Humanoid #DataCollection #AGI #Dance

Unitree

197,278 views • 1 year ago

Researchers developed a system called LATENT that teaches humanoid robots to play tennis using small pieces of human movement data. It learns basic motion fragments, then corrects and combines them to create natural movements and swings. The system was tested on the Unitree G1 humanoid robot, enabling it to hit balls and rally with human players.

Researchers developed a system called LATENT that teaches humanoid robots to play tennis using small pieces of human movement data. It learns basic motion fragments, then corrects and combines them to create natural movements and swings. The system was tested on the Unitree G1 humanoid robot, enabling it to hit balls and rally with human players.

Space and Technology

45,748 views • 2 months ago

🚨MEET THE UNITREE G1 HUMANOID Priced between $12,500 and $16,000, it's designed for sports and physical tasks, with 23 to 43 joints for dynamic movement. Its hands, equipped with 2 fingers and a thumb, handle objects with precision. Scared yet?

🚨MEET THE UNITREE G1 HUMANOID Priced between $12,500 and $16,000, it's designed for sports and physical tasks, with 23 to 43 joints for dynamic movement. Its hands, equipped with 2 fingers and a thumb, handle objects with precision. Scared yet?

Mario Nawfal

248,592 views • 2 years ago

🤖 Ever dreamed of controlling a humanoid robot to perform complex, long-horizon tasks — using just a single Vision Pro? 🎉 Meet CLONE: a holistic, closed-loop, whole-body teleoperation system for long-horizon humanoid control! 🏃‍♂️🧍 CLONE enables rich and coordinated interactive tasks: 🥊 boxing 🏓 table tennis 🤲 object pickup 📦 room arrangement 🤝 handover … and more! 🌀 Our closed-loop error correction powered by LiDAR odometry ensures precision, while motion-captured demonstrations supercharge policy learning — unlocking the full potential of the G1 robot. 🎥 It’s hard to squeeze the magic into 1 minute — check out the full video demo and project page here: 🔗

🤖 Ever dreamed of controlling a humanoid robot to perform complex, long-horizon tasks — using just a single Vision Pro? 🎉 Meet CLONE: a holistic, closed-loop, whole-body teleoperation system for long-horizon humanoid control! 🏃‍♂️🧍 CLONE enables rich and coordinated interactive tasks: 🥊 boxing 🏓 table tennis 🤲 object pickup 📦 room arrangement 🤝 handover … and more! 🌀 Our closed-loop error correction powered by LiDAR odometry ensures precision, while motion-captured demonstrations supercharge policy learning — unlocking the full potential of the G1 robot. 🎥 It’s hard to squeeze the magic into 1 minute — check out the full video demo and project page here: 🔗

Siyuan Huang

66,737 views • 1 year ago

If you have 10 kids it’s time to give them each chores so that you can at least keep up with the day-to-day routines. Washing dishes, doing laundry, cleaning the house etc. I had chores as a kid I dusted the house, vacuumed and did the dishes on certain day.

If you have 10 kids it’s time to give them each chores so that you can at least keep up with the day-to-day routines. Washing dishes, doing laundry, cleaning the house etc. I had chores as a kid I dusted the house, vacuumed and did the dishes on certain day.

Suzee Q

24,746 views • 1 month ago

Researchers developed Hitter, a humanoid robot that can play table tennis in real-world settings. It was trained on the Unitree G1 robot to predict the ball’s path, choose the right shot, and react in less than a second. In tests, it achieved 106 consecutive shots with a human and even rallied with another humanoid robot.

Researchers developed Hitter, a humanoid robot that can play table tennis in real-world settings. It was trained on the Unitree G1 robot to predict the ball’s path, choose the right shot, and react in less than a second. In tests, it achieved 106 consecutive shots with a human and even rallied with another humanoid robot.

Space and Technology

25,736 views • 3 months ago

The problem with humanoid teleoperation is that it is expensive and difficult to scale Enter NVIDIA's EgoScale: - A VLA model pretrained on thousands hours of egocentric human videos. - Mid-trained via 50 hours of human + 4 hours of robot "play" data for human-robot alignment. - Fine-tuned with very few examples of task-specific robot teleoperation (100 or fewer per task). - Successfully transfers across 5-finger (Sharpa) and 3-finger (Unitree G1) robot hands. - Performance scales predictably as data increases.

The problem with humanoid teleoperation is that it is expensive and difficult to scale Enter NVIDIA's EgoScale: - A VLA model pretrained on thousands hours of egocentric human videos. - Mid-trained via 50 hours of human + 4 hours of robot "play" data for human-robot alignment. - Fine-tuned with very few examples of task-specific robot teleoperation (100 or fewer per task). - Successfully transfers across 5-finger (Sharpa) and 3-finger (Unitree G1) robot hands. - Performance scales predictably as data increases.

The Humanoid Hub

44,441 views • 5 months ago

Meet Any2Track, a new two-stage RL framework designed to address a core challenge for humanoid robots: reliably tracking diverse, dynamic motions in the real world. The framework consists of two key components: AnyTracker, a general motion tracker, and AnyAdapter, a module that allows the robot to adapt to real-world disturbances like uneven terrain or external forces. This approach gives robots the stability needed for practical use. The system has been successfully deployed on a Unitree G1 humanoid robot with zero-shot sim2real transfer, performing exceptionally well in various motion tracking tasks under multiple real-world disturbances. Project: Codebase:

Meet Any2Track, a new two-stage RL framework designed to address a core challenge for humanoid robots: reliably tracking diverse, dynamic motions in the real world. The framework consists of two key components: AnyTracker, a general motion tracker, and AnyAdapter, a module that allows the robot to adapt to real-world disturbances like uneven terrain or external forces. This approach gives robots the stability needed for practical use. The system has been successfully deployed on a Unitree G1 humanoid robot with zero-shot sim2real transfer, performing exceptionally well in various motion tracking tasks under multiple real-world disturbances. Project: Codebase:

RoboHub🤖

61,378 views • 10 months ago

🤖 China unveils a humanoid robot priced at $1,400 Beijing-based company Noetix Robotics has introduced a compact humanoid robot named Bumi, priced at around $1,400, South China Morning Post reports. The affordable price could be a breakthrough for the industry, making robots accessible not only to companies but also to ordinary people. For comparison, previous Chinese models like Unitree R1 cost nearly $6,000. Bumi can perform simple tasks and assist with household chores or education. Would you get one as your personal helper?

🤖 China unveils a humanoid robot priced at $1,400 Beijing-based company Noetix Robotics has introduced a compact humanoid robot named Bumi, priced at around $1,400, South China Morning Post reports. The affordable price could be a breakthrough for the industry, making robots accessible not only to companies but also to ordinary people. For comparison, previous Chinese models like Unitree R1 cost nearly $6,000. Bumi can perform simple tasks and assist with household chores or education. Would you get one as your personal helper?

NEXTA

56,573 views • 9 months ago

People still say humanoid robots cannot handle creativity, rhythm, or coordinated motion. Meanwhile, a Unitree humanoid is already playing drums with timing, arm synchronization, balance control, and real time motion planning. Here is why this matters: Goldman Sachs projects the humanoid robot market could reach $38 billion by 2035, with shipments around 1.4 million units. Unitree’s R1 started around $5,600, while its earlier G1 was around $16,000, showing how fast humanoid hardware costs are falling. A drum performance may look like entertainment, but it tests the same foundations robotics needs everywhere: motion control latency balance precision spatial awareness task repetition A robot does not need to become human to start replacing human tasks. It only needs to become good enough. And that line is getting closer every year.

People still say humanoid robots cannot handle creativity, rhythm, or coordinated motion. Meanwhile, a Unitree humanoid is already playing drums with timing, arm synchronization, balance control, and real time motion planning. Here is why this matters: Goldman Sachs projects the humanoid robot market could reach $38 billion by 2035, with shipments around 1.4 million units. Unitree’s R1 started around $5,600, while its earlier G1 was around $16,000, showing how fast humanoid hardware costs are falling. A drum performance may look like entertainment, but it tests the same foundations robotics needs everywhere: motion control latency balance precision spatial awareness task repetition A robot does not need to become human to start replacing human tasks. It only needs to become good enough. And that line is getting closer every year.

TechniaHQ | humanoid robots

22,630 views • 2 months ago

More and more humanoid robot kiosks are appearing in China. Yesterday, I passed by a subway entrance in Guangzhou and experienced a retail kiosk operated by a humanoid robot again, buying a bottle of water. The process was the same: select items on a screen, scan a QR code for mobile payment, and the humanoid robot retrieves the product. (However, it didn't interact with me at all.) I looked it up, and the wheeled humanoid robot is named S1, from AutoLife Robotics in Shenzhen. It uses omnidirectional wheels for movement and a lifting body. It's 1-1.6m tall, weighs 72kg, and has a 10-hour battery life. A single arm can carry 3-5kg. Furthermore, this humanoid robot is suitable for lightweight tasks in retail, convenience stores, supermarkets, and warehouse sorting.

More and more humanoid robot kiosks are appearing in China. Yesterday, I passed by a subway entrance in Guangzhou and experienced a retail kiosk operated by a humanoid robot again, buying a bottle of water. The process was the same: select items on a screen, scan a QR code for mobile payment, and the humanoid robot retrieves the product. (However, it didn't interact with me at all.) I looked it up, and the wheeled humanoid robot is named S1, from AutoLife Robotics in Shenzhen. It uses omnidirectional wheels for movement and a lifting body. It's 1-1.6m tall, weighs 72kg, and has a 10-hour battery life. A single arm can carry 3-5kg. Furthermore, this humanoid robot is suitable for lightweight tasks in retail, convenience stores, supermarkets, and warehouse sorting.

CyberRobo

52,565 views • 4 months ago

In just one week, Binh Pham and I trained a full-body Unitree G1. Here's a recap: 1. Secured a Unitree G1 humanoid through a LinkedIn post 2. Deployed TWIST2 full-body teleoperation pipelines 3. Adapted TWIST2 for Zed stereo camera & collected full-body teleoperation samples (carried by Binh Pham ) 4. Adapted & fine-tuned NVIDIA Gr00T N1.5 VLA on the TWIST2 public datasets, which I fine-tuned on an 8xNVIDIA H100 Cluster. We picked Gr00T N1.5 as it was trained with Unitree G1 embodiment data. 5. Adapted the TWIST2 codebase to stream in the actions from Gr00T via ZMQ using a co-located NVIDIA H100 for ~200ms inference latency 6. Tested the model in sim, then deployed to the real-world Unitree G1. We streamed a training sample observation to the VLA (as we didn't want to break robot in case real observations were OOD) We were the first team in the world to deploy the full TWIST2 data collection pipeline to the unitree g1 :) Much more work ahead though, which I'll work on as a side-project over the next months: 1. Exploring the various types of 'world models': video backbones, dynamics models, v-jepa-2 models. I believe these will generalize better & train much more data-efficiently than VLM backbones 2. Speeding up inference - I believe low-latency robotics inference will be a big challenge. There are many works in video diffusion which I'd like to test (e.g. SageAttention, SparseAttention, Drifting Models). Perhaps also writing custom CUDA kernels. 3. Economics of inference scaling :) What will be the compute demands as we scale inference up to millions of humanoids? Will it run on edge or on distributed 'co-located' inference clusters? These are questions I'd like to answer. Adapted TWIST2 codebase: Adapted Gr00T-N1.5 codebase: The ETH Robotics Club are doing a cool GTC Golden ticket competition with NVIDIA , so this is my submission :) The DGX Spark compute will get me a long way with initial prototyping & especially working on inference optimization for next-gen Blackwell GPUs #NVIDIAGTC #GOLDENTICKET #ETHRC

In just one week, Binh Pham and I trained a full-body Unitree G1. Here's a recap: 1. Secured a Unitree G1 humanoid through a LinkedIn post 2. Deployed TWIST2 full-body teleoperation pipelines 3. Adapted TWIST2 for Zed stereo camera & collected full-body teleoperation samples (carried by Binh Pham ) 4. Adapted & fine-tuned NVIDIA Gr00T N1.5 VLA on the TWIST2 public datasets, which I fine-tuned on an 8xNVIDIA H100 Cluster. We picked Gr00T N1.5 as it was trained with Unitree G1 embodiment data. 5. Adapted the TWIST2 codebase to stream in the actions from Gr00T via ZMQ using a co-located NVIDIA H100 for ~200ms inference latency 6. Tested the model in sim, then deployed to the real-world Unitree G1. We streamed a training sample observation to the VLA (as we didn't want to break robot in case real observations were OOD) We were the first team in the world to deploy the full TWIST2 data collection pipeline to the unitree g1 :) Much more work ahead though, which I'll work on as a side-project over the next months: 1. Exploring the various types of 'world models': video backbones, dynamics models, v-jepa-2 models. I believe these will generalize better & train much more data-efficiently than VLM backbones 2. Speeding up inference - I believe low-latency robotics inference will be a big challenge. There are many works in video diffusion which I'd like to test (e.g. SageAttention, SparseAttention, Drifting Models). Perhaps also writing custom CUDA kernels. 3. Economics of inference scaling :) What will be the compute demands as we scale inference up to millions of humanoids? Will it run on edge or on distributed 'co-located' inference clusters? These are questions I'd like to answer. Adapted TWIST2 codebase: Adapted Gr00T-N1.5 codebase: The ETH Robotics Club are doing a cool GTC Golden ticket competition with NVIDIA , so this is my submission :) The DGX Spark compute will get me a long way with initial prototyping & especially working on inference optimization for next-gen Blackwell GPUs #NVIDIAGTC #GOLDENTICKET #ETHRC

Arnie Ramesh

14,815 views • 5 months ago

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

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

RoboPapers

27,249 views • 3 months ago

The Unitree G1 is stepping onto the court, demonstrating the ability to sustain multi-shot tennis rallies with human players. A research team from Tsinghua and Peking University developed the LATENT system, which allows the humanoid to return balls traveling at over 15 m/s. By training on "imperfect" motion fragments and applying corrective adjustments, the robot maintains an athletic, human-like style during high-speed play.

The Unitree G1 is stepping onto the court, demonstrating the ability to sustain multi-shot tennis rallies with human players. A research team from Tsinghua and Peking University developed the LATENT system, which allows the humanoid to return balls traveling at over 15 m/s. By training on "imperfect" motion fragments and applying corrective adjustments, the robot maintains an athletic, human-like style during high-speed play.

Humanoids daily

15,267 views • 4 months ago

Kinetix AI has teased KAI, its new humanoid robot -engineered with 36 degrees of freedom, more than any previous model, a hybrid dexterous hand, and 18,000 sensors embedded across a soft, flexible body-positioning it as the most human-like robotic system to date. Getting closer to real humanoid robots each day.

Kinetix AI has teased KAI, its new humanoid robot -engineered with 36 degrees of freedom, more than any previous model, a hybrid dexterous hand, and 18,000 sensors embedded across a soft, flexible body-positioning it as the most human-like robotic system to date. Getting closer to real humanoid robots each day.

Chubby♨️

22,473 views • 3 months ago

We’ve all seen videos of humanoid robots performing single tasks that are very impressive, like dancing or karate. But training humanoid robots to perform a wide range of complex motions is difficult. GMT is a general-purpose policy which can learn a wide range of robot motions. Watch Episode #32 of RoboPapers, with Zixuan Chen , co-hosted by Michael Cho - Rbt/Acc and Chris Paxton , to learn more.

We’ve all seen videos of humanoid robots performing single tasks that are very impressive, like dancing or karate. But training humanoid robots to perform a wide range of complex motions is difficult. GMT is a general-purpose policy which can learn a wide range of robot motions. Watch Episode #32 of RoboPapers, with Zixuan Chen , co-hosted by Michael Cho - Rbt/Acc and Chris Paxton , to learn more.

RoboPapers

16,605 views • 10 months ago

A new humanoid robot Spirit AI from China releases a new generation of wheeled humanoid robot Moz1 It is the first embodied intelligent robot with high-precision force control of the whole body, with 26 degrees of freedom, built based on the world's highest power density integrated force control joint. It takes speed, precision and safety to a higher level. It is worth mentioning that Moz1 is driven by SpiritAI's latest OneTwoVLA. It only needs one model to think and operate at the same time, and correct errors autonomously, just like humans, without separating the two systems of "thinking planning" and "coordinated execution". One system is seamlessly connected, which is conducive to dealing with complex, personalized, and immediate tasks, especially in home and care applications.

A new humanoid robot Spirit AI from China releases a new generation of wheeled humanoid robot Moz1 It is the first embodied intelligent robot with high-precision force control of the whole body, with 26 degrees of freedom, built based on the world's highest power density integrated force control joint. It takes speed, precision and safety to a higher level. It is worth mentioning that Moz1 is driven by SpiritAI's latest OneTwoVLA. It only needs one model to think and operate at the same time, and correct errors autonomously, just like humans, without separating the two systems of "thinking planning" and "coordinated execution". One system is seamlessly connected, which is conducive to dealing with complex, personalized, and immediate tasks, especially in home and care applications.

CyberRobo

26,755 views • 1 year ago

Another headless wheeled humanoid Shenzhen VLAI Robotics just released a pretty pragmatic humanoid robot called L1. I checked the price, starting at RMB 28,800($4,188). wheeled base + height-adjustable dual arms.Anyone can be built into a household assistant:fetching water, tidying up the kitchen and living room, doing laundry, and more. >Dual arms with 16 DOF, bionic-style structure, capable of relatively fine tasks like grasping and plug-in operations >Adjustable arm height (~70–160 cm), covering both tabletop and standing work >Differential-drive wheeled base, 100 kg payload, simple but well-suited for indoor use, supports working while moving >Open interfaces + teleoperation/data collection. L1 feels more like a development platform than a finished product Beyond household humanoids, developers can build specialized humanoid robots tailored to a wide range of scenarios,from scientific research and manufacturing to warehousing, retail, and caregiving... We’re already seeing quite a few robots in this form factor. While some are pushing toward full humanoids, this “less-human” approach might actually reach real-world deployment sooner. --- (Shenzhen truly is a home for humanoid robots,it seems as though a new humanoid robot company could spring into existence at any moment.）

Another headless wheeled humanoid Shenzhen VLAI Robotics just released a pretty pragmatic humanoid robot called L1. I checked the price, starting at RMB 28,800($4,188). wheeled base + height-adjustable dual arms.Anyone can be built into a household assistant:fetching water, tidying up the kitchen and living room, doing laundry, and more. >Dual arms with 16 DOF, bionic-style structure, capable of relatively fine tasks like grasping and plug-in operations >Adjustable arm height (~70–160 cm), covering both tabletop and standing work >Differential-drive wheeled base, 100 kg payload, simple but well-suited for indoor use, supports working while moving >Open interfaces + teleoperation/data collection. L1 feels more like a development platform than a finished product Beyond household humanoids, developers can build specialized humanoid robots tailored to a wide range of scenarios,from scientific research and manufacturing to warehousing, retail, and caregiving... We’re already seeing quite a few robots in this form factor. While some are pushing toward full humanoids, this “less-human” approach might actually reach real-world deployment sooner. --- (Shenzhen truly is a home for humanoid robots,it seems as though a new humanoid robot company could spring into existence at any moment.）

CyberRobo

38,538 views • 4 months ago