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Launching Dimensional: the operating system for physical space Command any robot in natural language, with universal abilities like spatial memory, autonomous navigation, manipulation, person tracking, more. Open source. Single pip install It’s time to program atoms, not bits

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251,136 次观看 • 8 个月前 •via X (Twitter)

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Announcing Dimensional: the open-source OS for physical space. Command any robot in natural language. Program atoms, not bits.

Announcing Dimensional: the open-source OS for physical space. Command any robot in natural language. Program atoms, not bits.

stash

193,375 次观看 • 8 个月前

Openclaw / Agents can now command ANY robot to grasp objects via language Integrate dimensional with your personal agent to unlock the physical world Fully open source. Join the hundreds of developers already vibecoding atoms

Openclaw / Agents can now command ANY robot to grasp objects via language Integrate dimensional with your personal agent to unlock the physical world Fully open source. Join the hundreds of developers already vibecoding atoms

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Introducing MARS, the first Personal AI Robot. In technology, getting to the future we want starts with building it together. This is why we designed Mars. Inspired by early PCs, Mars is a powerful, complete, extendable robot. It runs BASIC, an open embodied AI agent we created for you to program with code, demonstrations, and prompts. This allows Mars to perform complex long-horizon tasks involving spatial memory, reasoning, manipulation and navigation. Pre-orders open now ⬇️ Demos & details in the thread

Introducing MARS, the first Personal AI Robot. In technology, getting to the future we want starts with building it together. This is why we designed Mars. Inspired by early PCs, Mars is a powerful, complete, extendable robot. It runs BASIC, an open embodied AI agent we created for you to program with code, demonstrations, and prompts. This allows Mars to perform complex long-horizon tasks involving spatial memory, reasoning, manipulation and navigation. Pre-orders open now ⬇️ Demos & details in the thread

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Language models process data as one-dimensional sequences of tokens — ideal for text, but limited for understanding the physical world. In contrast, spatial intelligence embraces a 3D representation, unlocking a deeper understanding of space and time. More from martin_casado's interview with Fei-Fei Li and Justin Johnson:

Language models process data as one-dimensional sequences of tokens — ideal for text, but limited for understanding the physical world. In contrast, spatial intelligence embraces a 3D representation, unlocking a deeper understanding of space and time. More from martin_casado's interview with Fei-Fei Li and Justin Johnson:

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How do you give a humanoid the general motion capability? Not just single motions, but all motion? Introducing SONIC, our new work on supersizing motion tracking for natural humanoid control. We argue that motion tracking is the scalable foundation task for humanoids. So we "supersized" it: 9k+ GPU hours and 100M+ motion frames. But tracking alone is not enough; we show how to make a useful control system out of it: - Universal Kinematic Planner: Enables game-like gamepad control and high-level teleoperation, just like controlling a character in a game. - VR Full-Body Teleop: Direct, real-time whole-body control by a human wearing a VR headset. - VR Keypoint Teleop: Control the upper body (hands/head) while our planner handles robust locomotion automatically. - VLA Integration: We connect this motion tracker to autonomous Visual-Language-Action (VLA) models for autonomous task execution! We use a Universal Token Space to UNIFY this command space, turning our robust tracker into a general-purpose, programmable humanoid brain. This is the generalist "System 1" for humanoids. 🚀 Project: #Humanoids #Robotics #AI #FoundationModels #NVIDIAResearch 🧠🔥

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Hao Zhao

17,048 次观看 • 1 个月前

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Vaishnavi

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Johannes Tscharn

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Dustin

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Enough with LLMs - exciting things are happening in the world of atoms. This is Stanford ALOHA, a low-cost and agile robot platform. The whole system is open-source (!!): hardware design, CAD models for 3D printing, simulator, and training code. Time to graft a physical arm onto GPTs 🦾 Led by my friend Tony Zhao at Stanford, and advised by Chelsea Finn Sergey Levine Vikash Kumar. Project page: If you don't want to 3D print your own components, you can buy the setup at

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Scaling vision-language-action (VLA) models to high-DoF dexterous hands has long been a "holy grail" challenge due to the high-dimensional action space and data scarcity. As a wrap up of the year 2025, we are releasing GR-Dexter, a holistic hardware-model-data framework for generalist manipulation on a bimanual dexterous-hand robot. This is the first VLA system to achieve: ✅ High-DoF Control: Managing a 56-DoF bimanual system (21-DoF per hand). ✅ Long-Horizon Tasks with tool use: Vacuuming, bread serving with tongs, and table decluttering. ✅ Open-World Generalization: Robust performance with unseen objects and abstract instructions. Project page: ArXiv:

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🇬🇧 POLICE DRONES THAT ARRIVE BEFORE HUMANS Before an officer even gets the call, a drone could already be watching. Under the “Drone as First Responder” program, machines will launch from rooftop boxes. Racing to incidents in under 2 minutes, streaming real-time footage straight to command centers. Officials say it’s for safety and evidence. But with cameras always on, and eyes in the sky before people on the ground, it feels less like help is on the way, and more like someone always is. With people getting arrested in the UK for Facebook posts, what happens when there’s a drone on every corner? Source: Open Source Intel

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130,753 次观看 • 9 个月前

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Colby Adcock

213,401 次观看 • 5 个月前

🚀Exciting News! We’re thrilled to introduce OpenWBT — the open-source, whole-body VR teleoperation system designed for humanoid across various robot types & virtual/physical worlds! 🤖✨ 💡Developed through collaboration between Galbot and Tsinghua University researchers! 🔥 Why it’s cool? ✅ Multi-robot support – Control different types of bots with one system! ✅ Cross virtual & real worlds – Operate bots seamlessly in simulator and the physical world. ✅ Built for YOU – Quick deployment with only a laptop and a VR headset, and create like never before! 💡 Calling all robot lovers & devs! Download, experiment, and help shape the future of robotics. Let’s #BuildTheFuture together! 🔗 Grab it now: GitHub： Welcome to our website： #OpenWBT #Robotics #OpenSource #Innovation #HumanoidRobots

🚀Exciting News! We’re thrilled to introduce OpenWBT — the open-source, whole-body VR teleoperation system designed for humanoid across various robot types & virtual/physical worlds! 🤖✨ 💡Developed through collaboration between Galbot and Tsinghua University researchers! 🔥 Why it’s cool? ✅ Multi-robot support – Control different types of bots with one system! ✅ Cross virtual & real worlds – Operate bots seamlessly in simulator and the physical world. ✅ Built for YOU – Quick deployment with only a laptop and a VR headset, and create like never before! 💡 Calling all robot lovers & devs! Download, experiment, and help shape the future of robotics. Let’s #BuildTheFuture together! 🔗 Grab it now: GitHub： Welcome to our website： #OpenWBT #Robotics #OpenSource #Innovation #HumanoidRobots

Galbot

38,356 次观看 • 1 年前

Excited to announce GR00T N1, the world’s first open foundation model for humanoid robots! We are on a mission to democratize Physical AI. The power of general robot brain, in the palm of your hand - with only 2B parameters, N1 learns from the most diverse physical action dataset ever compiled and punches above its weight: - Real humanoid teleoperation data. - Large-scale simulation data: we are open-sourcing 300K+ trajectories! - Neural trajectories: we apply SOTA video generation models to “hallucinate” new synthetic data that features accurate physics in pixels. Using Jensen’s words, “systematically infinite data”! - Latent actions: we develop novel algorithms to extract action tokens from in-the-wild human videos and neural generated videos. GR00T N1 is a single end-to-end neural net, from photons to actions: - Vision-Language Model (System 2) that interprets the physical world through vision and language instructions, enabling robots to reason about their environment and instructions, and plan the right actions. - Diffusion Transformer (System 1) that “renders” smooth and precise motor actions at 120 Hz, executing the latent plan made by System 2. We deploy N1 on GR1 robot, 1X Neo robot, and a large collection of simulation benchmarks. N1 achieves up to +30% boost in diverse manipulation tasks for household and industrial settings. While humanoid robots are the main focus of N1, our model also supports cross-embodiment. We finetune it to work on the $110 HuggingFace LeRobot SO100 robot arm! Open robot brain runs on open hardware. Sounds just right. Let’s solve robotics, together, one token at a time. Links to our Whitepaper, Github repo, HuggingFace model, and open dataset page in the thread: 🧵

Excited to announce GR00T N1, the world’s first open foundation model for humanoid robots! We are on a mission to democratize Physical AI. The power of general robot brain, in the palm of your hand - with only 2B parameters, N1 learns from the most diverse physical action dataset ever compiled and punches above its weight: - Real humanoid teleoperation data. - Large-scale simulation data: we are open-sourcing 300K+ trajectories! - Neural trajectories: we apply SOTA video generation models to “hallucinate” new synthetic data that features accurate physics in pixels. Using Jensen’s words, “systematically infinite data”! - Latent actions: we develop novel algorithms to extract action tokens from in-the-wild human videos and neural generated videos. GR00T N1 is a single end-to-end neural net, from photons to actions: - Vision-Language Model (System 2) that interprets the physical world through vision and language instructions, enabling robots to reason about their environment and instructions, and plan the right actions. - Diffusion Transformer (System 1) that “renders” smooth and precise motor actions at 120 Hz, executing the latent plan made by System 2. We deploy N1 on GR1 robot, 1X Neo robot, and a large collection of simulation benchmarks. N1 achieves up to +30% boost in diverse manipulation tasks for household and industrial settings. While humanoid robots are the main focus of N1, our model also supports cross-embodiment. We finetune it to work on the $110 HuggingFace LeRobot SO100 robot arm! Open robot brain runs on open hardware. Sounds just right. Let’s solve robotics, together, one token at a time. Links to our Whitepaper, Github repo, HuggingFace model, and open dataset page in the thread: 🧵

Jim Fan

466,226 次观看 • 1 年前

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𝗪𝗵𝗮𝘁 𝗶𝗳 𝘆𝗼𝘂 𝗰𝗼𝘂𝗹𝗱 𝗴𝗼 𝗳𝗿𝗼𝗺 𝘁𝗲𝗹𝗲𝗼𝗽𝗲𝗿𝗮𝘁𝗶𝗻𝗴 𝗮 𝗿𝗼𝗯𝗼𝘁 𝘁𝗼 𝗱𝗲𝗽𝗹𝗼𝘆𝗶𝗻𝗴 𝗮 𝘁𝗿𝗮𝗶𝗻𝗲𝗱 𝗔𝗜 𝗽𝗼𝗹𝗶𝗰𝘆 𝗶𝗻 𝗹𝗲𝘀𝘀 𝘁𝗶𝗺𝗲 𝘁𝗵𝗮𝗻 𝗶𝘁 𝘁𝗮𝗸𝗲𝘀 𝘁𝗼 𝘄𝗮𝘁𝗰𝗵 𝗮 𝗺𝗼𝘃𝗶𝗲? Today, we're excited to open source our complete example showing exactly that: using Neuracore with the Piper robot from AgileX Robotics. What’s included: • 𝗠𝗲𝘁𝗮 𝗤𝘂𝗲𝘀𝘁 𝘁𝗲𝗹𝗲𝗼𝗽𝗲𝗿𝗮𝘁𝗶𝗼𝗻 – Control your robot with VR • 𝗘𝗻𝗱-𝘁𝗼-𝗲𝗻𝗱 𝘄𝗼𝗿𝗸𝗳𝗹𝗼𝘄 – Demo collection to model training to policy deployment • 𝗥𝗢𝗦 𝘃𝗶𝘀𝘂𝗮𝗹𝗶𝘇𝗲𝗿 – See your headset data with a single command • 𝗢𝗽𝗲𝗻 𝘀𝗼𝘂𝗿𝗰𝗲 𝗠𝗲𝘁𝗮 𝗤𝘂𝗲𝘀𝘁 𝘁𝗲𝗹𝗲𝗼𝗽 𝗽𝗮𝗰𝗸𝗮𝗴𝗲 – Works with any ROS-enabled robot If you have a Piper robot, grab the example, sign up for Neuracore, and show us what you build. Repo: Learn more: Open Robotics Meta Quest

Neuracore

21,894 次观看 • 6 个月前

Just collecting manipulation data isn’t enough for robots - they need to be able to move around in the world, which has a whole different set of challenges from pure manipulation. And bringing navigation and manipulation together in a single framework is even more challenging. Enter HERMES, from Zhecheng Yuan and Tianming Wei. This is a four-stage process in which human videos are used to set up an RL sim-to-real training pipeline in order to overcome differences between robot and human kinematics, and used together with a navigation foundation model to move around in a variety of environments. To learn more, join us as Zhecheng Yuan and Tianming Wei tell us about how they built their system to perform mobile dexterous manipulation from human videos in a variety of environments. Watch Episode #45 of RoboPapers today, hosted by Michael Cho - Rbt/Acc and Chris Paxton!

Just collecting manipulation data isn’t enough for robots - they need to be able to move around in the world, which has a whole different set of challenges from pure manipulation. And bringing navigation and manipulation together in a single framework is even more challenging. Enter HERMES, from Zhecheng Yuan and Tianming Wei. This is a four-stage process in which human videos are used to set up an RL sim-to-real training pipeline in order to overcome differences between robot and human kinematics, and used together with a navigation foundation model to move around in a variety of environments. To learn more, join us as Zhecheng Yuan and Tianming Wei tell us about how they built their system to perform mobile dexterous manipulation from human videos in a variety of environments. Watch Episode #45 of RoboPapers today, hosted by Michael Cho - Rbt/Acc and Chris Paxton!

RoboPapers

15,085 次观看 • 8 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

31,214 次观看 • 3 个月前