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Why Open-source With Isaac sim, GR00T, SmolVLA, 660$ XLeRobot can organize stuff into drawer and zipping up bag in 2 days Made by MakerMods Isaac Sin QI LIU Ryan Chan on Seeed Studio Hugging Face NVIDIA Robotics Home Robot Hackathon in Shenzhen (Bay Area next)

Vector Wang

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18,716 次观看 • 9 个月前 •via X (Twitter)

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Physics AI 🌊 Jensen just unveiled the NVIDIA Isaac GR00T Reference Humanoid Robot at GTC Taipei--the world’s first open-source humanoid robot reference design Built on Jetson Thor edge computing and the Isaac GR00T open platform, it features a Unitree H2 Plus body with Sharpa five-finger dexterous hands and 75 degrees of freedom. Even before Physical AI truly explodes, NVIDIA has built a complete end-to-end full-stack infrastructure: >chips (Jetson Thor + Blackwell), >synthetic data (GR00T-Dreams), >world models (Cosmos), >foundation models (GR00T N-series VLA), >high-fidelity simulation platforms (Isaac Sim + Isaac Lab + Omniverse). Dozens of humanoid robot companies ,including Agility Robotics, Aglie robotics,Boston Dynamics, Figure, 1X, NEURA Robotics, XPENG Robotics, and more are already running large-scale daily simulation training on this platform, rapidly iterating perception, reasoning, and actions in virtual environments, speeding up the jump from lab prototypes to real factory deployment. By providing an open reference design and full-stack tools, NVIDIA has dramatically lowered the barrier, letting every robotics team join the Physical AI wave with low cost and high efficiency.

Physics AI 🌊 Jensen just unveiled the NVIDIA Isaac GR00T Reference Humanoid Robot at GTC Taipei--the world’s first open-source humanoid robot reference design Built on Jetson Thor edge computing and the Isaac GR00T open platform, it features a Unitree H2 Plus body with Sharpa five-finger dexterous hands and 75 degrees of freedom. Even before Physical AI truly explodes, NVIDIA has built a complete end-to-end full-stack infrastructure: >chips (Jetson Thor + Blackwell), >synthetic data (GR00T-Dreams), >world models (Cosmos), >foundation models (GR00T N-series VLA), >high-fidelity simulation platforms (Isaac Sim + Isaac Lab + Omniverse). Dozens of humanoid robot companies ,including Agility Robotics, Aglie robotics,Boston Dynamics, Figure, 1X, NEURA Robotics, XPENG Robotics, and more are already running large-scale daily simulation training on this platform, rapidly iterating perception, reasoning, and actions in virtual environments, speeding up the jump from lab prototypes to real factory deployment. By providing an open reference design and full-stack tools, NVIDIA has dramatically lowered the barrier, letting every robotics team join the Physical AI wave with low cost and high efficiency.

CyberRobo

17,092 次观看 • 2 个月前

Jensen just unveiled the NVIDIA Isaac GR00T Reference Humanoid Robot at GTC Taipei, the first open humanoid reference design built on Jetson Thor + the Isaac GR00T platform. - The body: Unitree H2 chassis + Sharpa Wave tactile 5-finger hands. - The brain: Jetson Thor compute + the NVIDIA Isaac GR00T open software stack (teleop, foundation models, sim, ROS). - Aimed at academic labs that want to do frontier humanoid research without proprietary lock-in. - Early adopters: ETH Zurich, Stanford Robotics Center, UCSD ARCLab. Endorsed by Skild's Deepak Pathak and Ai2's Dieter Fox. Ships from Unitree late 2026.

Jensen just unveiled the NVIDIA Isaac GR00T Reference Humanoid Robot at GTC Taipei, the first open humanoid reference design built on Jetson Thor + the Isaac GR00T platform. - The body: Unitree H2 chassis + Sharpa Wave tactile 5-finger hands. - The brain: Jetson Thor compute + the NVIDIA Isaac GR00T open software stack (teleop, foundation models, sim, ROS). - Aimed at academic labs that want to do frontier humanoid research without proprietary lock-in. - Early adopters: ETH Zurich, Stanford Robotics Center, UCSD ARCLab. Endorsed by Skild's Deepak Pathak and Ai2's Dieter Fox. Ships from Unitree late 2026.

The Humanoid Hub

40,132 次观看 • 2 个月前

"Bring me the healthiest snack." The robot goes to the kitchen and gets the snack, fully autonomously. This is the first public demo of NVIDIA's Isaac GR00T N1.6 foundation model presented by Yuke Zhu at CoRL 2025. The previous versions focused only on bimanual stationary manipulation; the N1.6 unlocks the entire kinematic range of the robot. The latest release of the open Isaac GR00T N1.6 VLA model will be available soon on Hugging Face. It integrates with NVIDIA Cosmos Reason, an open, customizable reasoning vision language model that turns vague instructions into step-by-step plans.

"Bring me the healthiest snack." The robot goes to the kitchen and gets the snack, fully autonomously. This is the first public demo of NVIDIA's Isaac GR00T N1.6 foundation model presented by Yuke Zhu at CoRL 2025. The previous versions focused only on bimanual stationary manipulation; the N1.6 unlocks the entire kinematic range of the robot. The latest release of the open Isaac GR00T N1.6 VLA model will be available soon on Hugging Face. It integrates with NVIDIA Cosmos Reason, an open, customizable reasoning vision language model that turns vague instructions into step-by-step plans.

The Humanoid Hub

42,621 次观看 • 10 个月前

Big news! World Labs' Marble is officially compatible with NVIDIA Robotics' Isaac Sim. Instead of showcasing their highlight reel, our team at Lightwheel created a full environment from a 360 pano using Marble and showed you can train directly in sim. The only non-generated assets are the robot arms, coffee, and bowl. Everything else was generated with Marble. Not sure how to do this yourself? NVIDIA wrote a technical blog with full instructions. You will learn how to: 1. Export scenes from World Labs' Marble as Gaussian splats 2. Convert to USD using NVIDIA Omniverse NuRec 3. Import into NVIDIA Isaac Sim 4. Add a robot and run the simulation Read the guide ➡️ #WorldModels #Robotics

Big news! World Labs' Marble is officially compatible with NVIDIA Robotics' Isaac Sim. Instead of showcasing their highlight reel, our team at Lightwheel created a full environment from a 360 pano using Marble and showed you can train directly in sim. The only non-generated assets are the robot arms, coffee, and bowl. Everything else was generated with Marble. Not sure how to do this yourself? NVIDIA wrote a technical blog with full instructions. You will learn how to: 1. Export scenes from World Labs' Marble as Gaussian splats 2. Convert to USD using NVIDIA Omniverse NuRec 3. Import into NVIDIA Isaac Sim 4. Add a robot and run the simulation Read the guide ➡️ #WorldModels #Robotics

Jonathan Stephens

13,783 次观看 • 7 个月前

Jensen just announced Newton, an open-source physics engine for robotics simulation developed by NVIDIA, Google DeepMind, and Disney Research. ⦿ Built on NVIDIA Warp, it offers GPU-accelerated performance and compatibility with frameworks like MuJoCo and Isaac Lab. ⦿ Features differentiable physics, extensibility for multiphysics simulations, and integration with OpenUSD for flexible data modeling. ⦿ Newton addresses the sim-to-real gap by creating realistic virtual environments for robot training and testing. ⦿ Disney Research is using Newton to power next-gen entertainment robots, including Star Wars-inspired BDX droids.

Jensen just announced Newton, an open-source physics engine for robotics simulation developed by NVIDIA, Google DeepMind, and Disney Research. ⦿ Built on NVIDIA Warp, it offers GPU-accelerated performance and compatibility with frameworks like MuJoCo and Isaac Lab. ⦿ Features differentiable physics, extensibility for multiphysics simulations, and integration with OpenUSD for flexible data modeling. ⦿ Newton addresses the sim-to-real gap by creating realistic virtual environments for robot training and testing. ⦿ Disney Research is using Newton to power next-gen entertainment robots, including Star Wars-inspired BDX droids.

The Humanoid Hub

130,388 次观看 • 1 年前

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:

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 次观看 • 1 年前

This is what open robotics actually looks like! 🔓 I was in Bordeaux, sitting inside Pollen Robotics, and had a chance to play around with their humanoid robot Reachy 2. It’s expressive, modular, and can even bring you coffee, and of course runs Python or Rust. I was talking with Reachy in 3 different languages, tele-operating it and manipulating kitchen stuff, and make it even mimic my gestures. The best part is that there are no locked APIs, or hidden stuff, just an open platform that you can build upon. The connection with Hugging Face makes it super easy to start, as the open source approach allows everyone to contribute, experiment and add their own things. I already ordered his little brother Reachy Mini, let's see what a robotics rookie can do with that robot! 👀 ~~ ♻️ Join the weekly robotics newsletter, and never miss any news →

This is what open robotics actually looks like! 🔓 I was in Bordeaux, sitting inside Pollen Robotics, and had a chance to play around with their humanoid robot Reachy 2. It’s expressive, modular, and can even bring you coffee, and of course runs Python or Rust. I was talking with Reachy in 3 different languages, tele-operating it and manipulating kitchen stuff, and make it even mimic my gestures. The best part is that there are no locked APIs, or hidden stuff, just an open platform that you can build upon. The connection with Hugging Face makes it super easy to start, as the open source approach allows everyone to contribute, experiment and add their own things. I already ordered his little brother Reachy Mini, let's see what a robotics rookie can do with that robot! 👀 ~~ ♻️ Join the weekly robotics newsletter, and never miss any news →

Lukas Ziegler

19,433 次观看 • 7 个月前

Today I assembled the first batch of reBot DevArm in the U.S! First one on the planet! 🇺🇸⚙️ But this isn’t about a robot arm. This is about what happens when open source hits robotics. For years: •Hardware was locked •Robotics was expensive •Embodied AI was out of reach Now? Anyone can get their hands on: •6 DOF manipulation •Real precision (<0.2 mm repeatability) •Full stack access (ROS, Isaac Sim, LeRobot) This is how movements start. Not in labs. Not behind paywalls. But in the hands of builders. Massive respect to Seeed Studio for pushing true open-source robotics forward! We’re about to see: → Thousands of robot arms trained like athletes → Real-world datasets explode → Physical AI built in garages, not just research labs At SoloTech , this is the unlock we’ve been waiting for, training and deploying Physical AI skill models on real hardware, anywhere. No sims. No vaporware. No excuses. Production Grade Physical AI. Want to get access? Check out the Physical AI Gym in San Francisco or DM me.

Today I assembled the first batch of reBot DevArm in the U.S! First one on the planet! 🇺🇸⚙️ But this isn’t about a robot arm. This is about what happens when open source hits robotics. For years: •Hardware was locked •Robotics was expensive •Embodied AI was out of reach Now? Anyone can get their hands on: •6 DOF manipulation •Real precision (<0.2 mm repeatability) •Full stack access (ROS, Isaac Sim, LeRobot) This is how movements start. Not in labs. Not behind paywalls. But in the hands of builders. Massive respect to Seeed Studio for pushing true open-source robotics forward! We’re about to see: → Thousands of robot arms trained like athletes → Real-world datasets explode → Physical AI built in garages, not just research labs At SoloTech , this is the unlock we’ve been waiting for, training and deploying Physical AI skill models on real hardware, anywhere. No sims. No vaporware. No excuses. Production Grade Physical AI. Want to get access? Check out the Physical AI Gym in San Francisco or DM me.

Dhruv Diddi

31,439 次观看 • 4 个月前

💥 A 450M model just beat bigger VLAs on real robot tasks, and it’s 100% open source [📍 bookmark for later] Came across SmolVLA, a new vision-language-action model for robotics that’s compact, fast, and trained entirely on open community datasets from LeRobot via Hugging Face. What stood out to me is how it matches or outperforms much larger models like ACT using noisy, real-world community data instead of giant private datasets. Why it’s worth a look ✅ 26% performance boost from pretraining on open-source data ✅ Runs on consumer hardware, even a MacBook ✅ 30% faster responses with async inference and smart architecture tweaks ✅ Strong results across Meta-World, LIBERO, SO100, and SO101 ✅ Fully open source: weights, code, training pipeline, eval stack They also introduced smart efficiency tricks like using fewer visual tokens, pulling outputs from mid-layer, and separating perception from action to make it all run fast. SmolVLA is a strong case for what can happen when the robotics community shares data and builds in the open. Definitely worth keeping an eye on.

💥 A 450M model just beat bigger VLAs on real robot tasks, and it’s 100% open source [📍 bookmark for later] Came across SmolVLA, a new vision-language-action model for robotics that’s compact, fast, and trained entirely on open community datasets from LeRobot via Hugging Face. What stood out to me is how it matches or outperforms much larger models like ACT using noisy, real-world community data instead of giant private datasets. Why it’s worth a look ✅ 26% performance boost from pretraining on open-source data ✅ Runs on consumer hardware, even a MacBook ✅ 30% faster responses with async inference and smart architecture tweaks ✅ Strong results across Meta-World, LIBERO, SO100, and SO101 ✅ Fully open source: weights, code, training pipeline, eval stack They also introduced smart efficiency tricks like using fewer visual tokens, pulling outputs from mid-layer, and separating perception from action to make it all run fast. SmolVLA is a strong case for what can happen when the robotics community shares data and builds in the open. Definitely worth keeping an eye on.

Ilir Aliu - eu/acc

17,353 次观看 • 11 个月前

New episode: Spencer Huang is a Product Lead for NVIDIA Robotics, focusing on open-source simulation frameworks, synthetic data generation, and robot autonomy. Spencer breaks down RL breakthroughs unlocked by hardware, open-source simulation, synthetic data flywheels, the competitive landscape at the application layer, humanoid use cases, and more. 01:16 Favorite part of Jensen’s keynote 03:37 Sudden unlock of humanoid dance demos 07:17 Sim-to-real RL for manipulation 10:20 Open-source vs. proprietary tools 12:55 How developers can accelerate Cosmos 16:40 Competitive landscape at the application layer 20:57 Humanoids in home and care use cases

New episode: Spencer Huang is a Product Lead for NVIDIA Robotics, focusing on open-source simulation frameworks, synthetic data generation, and robot autonomy. Spencer breaks down RL breakthroughs unlocked by hardware, open-source simulation, synthetic data flywheels, the competitive landscape at the application layer, humanoid use cases, and more. 01:16 Favorite part of Jensen’s keynote 03:37 Sudden unlock of humanoid dance demos 07:17 Sim-to-real RL for manipulation 10:20 Open-source vs. proprietary tools 12:55 How developers can accelerate Cosmos 16:40 Competitive landscape at the application layer 20:57 Humanoids in home and care use cases

The Humanoid Hub

25,006 次观看 • 9 个月前

NVIDIA just gave every robotics beginner a cheat code. You don’t need expensive hardware. You don’t need to burn motors. You don’t need to break prototypes. You can skip all of that. Because you can build the entire robot… virtually. With Isaac Sim, you design everything in simulation: Chassis. Wheels. Joints. All running on real physics. You add sensors—RGB cameras, 2D LiDAR—so your robot can actually see. You wire up control systems using ROS 2 and OmniGraph. You stream live sensor data straight into RViz. And suddenly… You’re not guessing anymore. You’re thinking like a robot. That’s the real shift. Simulation isn’t just practice. It’s leverage. You iterate faster. You break nothing. You ship something that actually works—before touching the real world. If you’re trying to get into robotics or physical AI… This isn’t optional. This is the new starting line.

NVIDIA just gave every robotics beginner a cheat code. You don’t need expensive hardware. You don’t need to burn motors. You don’t need to break prototypes. You can skip all of that. Because you can build the entire robot… virtually. With Isaac Sim, you design everything in simulation: Chassis. Wheels. Joints. All running on real physics. You add sensors—RGB cameras, 2D LiDAR—so your robot can actually see. You wire up control systems using ROS 2 and OmniGraph. You stream live sensor data straight into RViz. And suddenly… You’re not guessing anymore. You’re thinking like a robot. That’s the real shift. Simulation isn’t just practice. It’s leverage. You iterate faster. You break nothing. You ship something that actually works—before touching the real world. If you’re trying to get into robotics or physical AI… This isn’t optional. This is the new starting line.

Nainsi Dwivedi

26,312 次观看 • 3 个月前

Another win for open-source robotics! 🔥 Hugging Face just released a fully open-source humanoid robot, and you can build one for $2,500. I'm a huge advocate of open-source in robotics space. Why? Robotics is too hard to solve alone. So lowering the entry point is crucial. Also, ROS proved open ecosystems create lasting industry standards. So let's have a look at the new member of humanoids family! LeRobot Humanoid is a 3D-printed, bipedal humanoid platform designed for real robot learning experiments. It's a complete and, buildable robot Anddddd yes, it's a full stack release: → Hardware files, bill of materials and full assembly documentation → Simulation assets and training environments → Runtime tools for calibration and real-world control → Sim-to-real identification pipeline When a part breaks, reprint it. When a design choice doesn't work, modify it and test again. The whole point is fast iteration on real hardware, not treating the robot as a fixed artefact. The timing is not a coincidence. As foundation models for robotics mature, the field desperately needs open physical platforms to train, validate and deploy them on. clem 🤗 LET'S GO!!! Build it here: ~~ ♻️ Join the weekly robotics newsletter, and never miss any news →

Another win for open-source robotics! 🔥 Hugging Face just released a fully open-source humanoid robot, and you can build one for $2,500. I'm a huge advocate of open-source in robotics space. Why? Robotics is too hard to solve alone. So lowering the entry point is crucial. Also, ROS proved open ecosystems create lasting industry standards. So let's have a look at the new member of humanoids family! LeRobot Humanoid is a 3D-printed, bipedal humanoid platform designed for real robot learning experiments. It's a complete and, buildable robot Anddddd yes, it's a full stack release: → Hardware files, bill of materials and full assembly documentation → Simulation assets and training environments → Runtime tools for calibration and real-world control → Sim-to-real identification pipeline When a part breaks, reprint it. When a design choice doesn't work, modify it and test again. The whole point is fast iteration on real hardware, not treating the robot as a fixed artefact. The timing is not a coincidence. As foundation models for robotics mature, the field desperately needs open physical platforms to train, validate and deploy them on. clem 🤗 LET'S GO!!! Build it here: ~~ ♻️ Join the weekly robotics newsletter, and never miss any news →

Lukas Ziegler

20,361 次观看 • 2 个月前

Build a humanoid robot yourself! 🪚 OpenArm is an open-source humanoid robot. It comes with full CAD, control code, firmware, and simulation tools, everything needed to build, modify, and operate it. The arms are designed to be compliant and backdrivable. Teleoperation is supported, with force feedback and real-time gravity compensation so operators can guide the arm naturally. Super important, on the simulation side, OpenArm works with platforms like MuJoCo and Isaac Sim, letting developers test policies in virtual environments before running on hardware. Assemble it yourself from a kit or get it prebuilt, the goal is accessibility for research labs, small teams, and enthusiasts. The project is run by Enactic in Tokyo, Japan, and aims to lower the barrier for experimenting with dexterous manipulation. Let's put robotics in mainstream! 🔥🔥 P.S. I put the project page in the comments!

Build a humanoid robot yourself! 🪚 OpenArm is an open-source humanoid robot. It comes with full CAD, control code, firmware, and simulation tools, everything needed to build, modify, and operate it. The arms are designed to be compliant and backdrivable. Teleoperation is supported, with force feedback and real-time gravity compensation so operators can guide the arm naturally. Super important, on the simulation side, OpenArm works with platforms like MuJoCo and Isaac Sim, letting developers test policies in virtual environments before running on hardware. Assemble it yourself from a kit or get it prebuilt, the goal is accessibility for research labs, small teams, and enthusiasts. The project is run by Enactic in Tokyo, Japan, and aims to lower the barrier for experimenting with dexterous manipulation. Let's put robotics in mainstream! 🔥🔥 P.S. I put the project page in the comments!

Lukas Ziegler

233,110 次观看 • 10 个月前

After building 25+ XLeRobots for hackathons, we redesigned almost every structural part except the arms and head. And we’re open sourcing the hardware upgrade behind our XLeRobot build. It’s the actual internal print file we use for customer builds and hackathons. We made it: Easier to print - complete .3mf with tested on Bambu P1S/P2S/H2S/H2D. Easier to build - square side-loaded nut traps that don't fall out during disassembly, snap-on driver board covers (no tools), dedicated USB hub mounts for clean cable routing, quick-release power bank mount, etc. More stable base - bearing-supported omni wheel modules so the axle is loaded from both sides, replacing the stock LeKiwi chassis that wobbles under full XLeRobot weight. Thanks to: Isaac Sin Mr Thompson 许运诚 QI LIU Vector Wang LeRobot GitHub repo in reply. Technical specs in thread. Here is what we updated:

After building 25+ XLeRobots for hackathons, we redesigned almost every structural part except the arms and head. And we’re open sourcing the hardware upgrade behind our XLeRobot build. It’s the actual internal print file we use for customer builds and hackathons. We made it: Easier to print - complete .3mf with tested on Bambu P1S/P2S/H2S/H2D. Easier to build - square side-loaded nut traps that don't fall out during disassembly, snap-on driver board covers (no tools), dedicated USB hub mounts for clean cable routing, quick-release power bank mount, etc. More stable base - bearing-supported omni wheel modules so the axle is loaded from both sides, replacing the stock LeKiwi chassis that wobbles under full XLeRobot weight. Thanks to: Isaac Sin Mr Thompson 许运诚 QI LIU Vector Wang LeRobot GitHub repo in reply. Technical specs in thread. Here is what we updated:

Ryan Chan

19,603 次观看 • 4 个月前

Do you think you could train a robot to fold clothes better than any other robotics team? Now is your chance to prove it...and win actual cash prizes! The 2026 LeHome Challenge is live! Here is the details: Phase 1: Train your best clothes folding policy in simulation with 4 garment types, each presenting unique manipulation challenges. The types of garments include long-sleeved tops, short-sleeved tops, long pants, and shorts. The simulation environment uses Lightwheel's physics accurate deformable assets and built on NVIDIA Omniverse's Isaac Sim/Lab. Submit your code by April 5th for a chance to win up to $2,000 and a SO-101 Arm Kit. Phase 2: The top 8 teams will compete in person at ICRA on June 4th to see who's policy performs best with real clothes. The top place team will take home $20,000! Learn more and sign up for the LeHome Challenge here: Robert Scoble Chris Paxton The Humanoid Hub Harrison Kinsley #Robotics

Do you think you could train a robot to fold clothes better than any other robotics team? Now is your chance to prove it...and win actual cash prizes! The 2026 LeHome Challenge is live! Here is the details: Phase 1: Train your best clothes folding policy in simulation with 4 garment types, each presenting unique manipulation challenges. The types of garments include long-sleeved tops, short-sleeved tops, long pants, and shorts. The simulation environment uses Lightwheel's physics accurate deformable assets and built on NVIDIA Omniverse's Isaac Sim/Lab. Submit your code by April 5th for a chance to win up to $2,000 and a SO-101 Arm Kit. Phase 2: The top 8 teams will compete in person at ICRA on June 4th to see who's policy performs best with real clothes. The top place team will take home $20,000! Learn more and sign up for the LeHome Challenge here: Robert Scoble Chris Paxton The Humanoid Hub Harrison Kinsley #Robotics

Jonathan Stephens

24,003 次观看 • 5 个月前

The future of home cleaning just landed in Shenzhen and it is walking right into your living room. 🤖🏠 X Square Robot and officially launched China’s first robot home service, moving embodied AI from the lab to your front door. When you book a cleaning on the app, a professional cleaner now shows up with an X Square robot partner to tag team the house. The human handles the tricky stuff that needs real judgment while the robot takes over repetitive tasks like wiping tables and tidying up surfaces. X Square is using an end to end foundation model which means the robot actually perceives and plans its own moves instead of just following a script. By testing in the messy reality of a real home, they are proving that if a robot can master a living room, it can handle almost any physical space. This pilot is part of a massive push to turn these machines into reliable partners that can actually assist in our daily lives.

The future of home cleaning just landed in Shenzhen and it is walking right into your living room. 🤖🏠 X Square Robot and officially launched China’s first robot home service, moving embodied AI from the lab to your front door. When you book a cleaning on the app, a professional cleaner now shows up with an X Square robot partner to tag team the house. The human handles the tricky stuff that needs real judgment while the robot takes over repetitive tasks like wiping tables and tidying up surfaces. X Square is using an end to end foundation model which means the robot actually perceives and plans its own moves instead of just following a script. By testing in the messy reality of a real home, they are proving that if a robot can master a living room, it can handle almost any physical space. This pilot is part of a massive push to turn these machines into reliable partners that can actually assist in our daily lives.

RoboHub🤖

101,350 次观看 • 4 个月前

First time ever we combined the Seeed Studio ReBot with the Unitree Robotics Go2! 🤖🐕 The future of Physical AI isn’t just about moving; it’s about interaction. By mounting the ReBot arm onto the Unitree Go2, we’ve created a mobile manipulator that moves beyond simple locomotion into true household utility. What can this combo do? 1. Utility: Grab a drink from the fridge and bring it to you. 2. Maintenance: Identify and pick up trash around the house autonomously. 3. Care: Assist the elderly and children in navigating home environments safely. We are moving past "cool robot dog demos" and into the era of functional, embodied intelligence that solves real-world problems. Join the Movement This build is officially part of our Solo Seven challenge, our global mission to activate the world’s most talented builders across seven cities. We’re kicking things off by bringing this hardware to the BETA Berkeley Hackathon. Come get hands-on access, see the "fridge-run" in person, and help us define the next chapter of SoloTech 📍 Where: Frontier Tower 🗓️ When: This Sunday, April 26th Luma: See you there! 🚀 #SoloSeven #PhysicalAI #Robotics #UnitreeGo2 #SeeedStudio #SoloTech #BETA #Innovation

First time ever we combined the Seeed Studio ReBot with the Unitree Robotics Go2! 🤖🐕 The future of Physical AI isn’t just about moving; it’s about interaction. By mounting the ReBot arm onto the Unitree Go2, we’ve created a mobile manipulator that moves beyond simple locomotion into true household utility. What can this combo do? 1. Utility: Grab a drink from the fridge and bring it to you. 2. Maintenance: Identify and pick up trash around the house autonomously. 3. Care: Assist the elderly and children in navigating home environments safely. We are moving past "cool robot dog demos" and into the era of functional, embodied intelligence that solves real-world problems. Join the Movement This build is officially part of our Solo Seven challenge, our global mission to activate the world’s most talented builders across seven cities. We’re kicking things off by bringing this hardware to the BETA Berkeley Hackathon. Come get hands-on access, see the "fridge-run" in person, and help us define the next chapter of SoloTech 📍 Where: Frontier Tower 🗓️ When: This Sunday, April 26th Luma: See you there! 🚀 #SoloSeven #PhysicalAI #Robotics #UnitreeGo2 #SeeedStudio #SoloTech #BETA #Innovation

Dhruv Diddi

20,709 次观看 • 3 个月前

Something must change in robotics! 😖 As more billion-dollar players enter the space, more systems are closing off. APIs move behind paywalls, platforms lock down, and robots turn into black boxes. Pollen Robotics is taking the opposite route. With Reachy 2, everything is open: the code, the CAD files, the ROS 2 interfaces, the communication stack. If you want to swap the camera, redesign the gripper, or fork the whole system, you can, and that’s the point. It creates a culture where universities can run real experiments without licensing drama, and startups can prototype without waiting for vendor permission. Clone it on GitHub. Add behaviors. Share datasets. Fork the models. Push improvements upstream. The Hugging Face influence is real. It’s two open ecosystems aligning around the same idea: robotics should be built by more than a handful of companies. It was so cool to meet the team behind Reachy 2 in Bordeaux! 🔥 ~~ ♻️ Join the weekly robotics newsletter, and never miss any news →

Something must change in robotics! 😖 As more billion-dollar players enter the space, more systems are closing off. APIs move behind paywalls, platforms lock down, and robots turn into black boxes. Pollen Robotics is taking the opposite route. With Reachy 2, everything is open: the code, the CAD files, the ROS 2 interfaces, the communication stack. If you want to swap the camera, redesign the gripper, or fork the whole system, you can, and that’s the point. It creates a culture where universities can run real experiments without licensing drama, and startups can prototype without waiting for vendor permission. Clone it on GitHub. Add behaviors. Share datasets. Fork the models. Push improvements upstream. The Hugging Face influence is real. It’s two open ecosystems aligning around the same idea: robotics should be built by more than a handful of companies. It was so cool to meet the team behind Reachy 2 in Bordeaux! 🔥 ~~ ♻️ Join the weekly robotics newsletter, and never miss any news →

Lukas Ziegler

21,046 次观看 • 8 个月前

No one could turn down a humanoid robot with human-like tactile sensitivity. JQ Industries equipped the Unitree G1 humanoid robot with a fabric-based electronic skin (piezoresistive flexible tactile sensors). A light touch can convert pressure, deformation, and slip into electrical signals, which are then processed by AI for real-time closed-loop control.(Integrates NVIDIA Isaac Sim) With this skin,humanoid robots start to behave more naturally: Touch sensing is no longer limited to dexterous hands,the entire body can feel, allowing the robot to stop or adjust posture instantly during collisions. It can also detect hugs, taps on the shoulder, or gentle touches, and respond in a softer, more human-like way. This matters especially in elder care and medical rehabilitation. A humanoid robot could gently help someone stand up, or control force precisely during assisted massage without harming the skin. Rigid mechanical systems deliver superhuman physical strength, while flexible sensing systems enable nuanced emotions. Electronic skin bridges high intelligence and high emotional intelligence.

No one could turn down a humanoid robot with human-like tactile sensitivity. JQ Industries equipped the Unitree G1 humanoid robot with a fabric-based electronic skin (piezoresistive flexible tactile sensors). A light touch can convert pressure, deformation, and slip into electrical signals, which are then processed by AI for real-time closed-loop control.(Integrates NVIDIA Isaac Sim) With this skin,humanoid robots start to behave more naturally: Touch sensing is no longer limited to dexterous hands,the entire body can feel, allowing the robot to stop or adjust posture instantly during collisions. It can also detect hugs, taps on the shoulder, or gentle touches, and respond in a softer, more human-like way. This matters especially in elder care and medical rehabilitation. A humanoid robot could gently help someone stand up, or control force precisely during assisted massage without harming the skin. Rigid mechanical systems deliver superhuman physical strength, while flexible sensing systems enable nuanced emotions. Electronic skin bridges high intelligence and high emotional intelligence.

CyberRobo

22,118 次观看 • 4 个月前