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🚀 AGIBOT Genie Sim 3.0: First LLM-Driven Open-Source Simulation Platform for Embodied AI @ CES 2026 Integrated with NVIDIA Isaac Sim, AGIBOT’s all-new Genie Sim 3.0 ( debuts at CES - delivering a unified toolchain for digital asset generation, scene generalization, data collection, and automated evaluation. Key highlights: ✅...

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AGIBOT

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19,578 görüntüleme • 9 ay önce •via X (Twitter)

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The AI Index profil fotoğrafı
The AI Index9 ay önce

Open source plus sim to real sounds great, curious how much actually transfers without hand tuning

Himanshu Kumar profil fotoğrafı
Himanshu Kumar9 ay önce

@AGIBOTofficial, LLM-driven simulation opens new avenues for embodied AI, especially with NVIDIA Isaac Sim integration.

Angel profil fotoğrafı
Angel9 ay önce

thank you!

Nikhil Deshpande profil fotoğrafı
Nikhil Deshpande9 ay önce

Simulation is becoming the control plane for embodied AI. LLM-driven, open simulation stacks are how robots learn faster, safer, and at scale — long before touching the real world.

Benzer Videolar

#AGIBOTAIWeek Day4: Introducing GE-Sim 2.0 (Genie Envisioner World Simulator 2.0) , a comprehensive embodied world simulator for robotic manipulation. By integrating future video generation, proprioceptive state estimation, and reward-based policy assessment, GE-Sim 2.0 moves beyond visual simulation toward an embodied world simulator with built-in evaluation capability, laying the foundation for a world-model-centric platform for closed-loop and interactive policy learning. It provides a practical framework for scalable evaluation and training of robotic manipulation policies. Project page: #AGIBOT #AGIBOTAIWeek #GenieEnvisioner #Robotics #visualsimulation
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#AGIBOTAIWeek Day4: Introducing GE-Sim 2.0 (Genie Envisioner World Simulator 2.0) , a comprehensive embodied world simulator for robotic manipulation. By integrating future video generation, proprioceptive state estimation, and reward-based policy assessment, GE-Sim 2.0 moves beyond visual simulation toward an embodied world simulator with built-in evaluation capability, laying the foundation for a world-model-centric platform for closed-loop and interactive policy learning. It provides a practical framework for scalable evaluation and training of robotic manipulation policies. Project page: #AGIBOT #AGIBOTAIWeek #GenieEnvisioner #Robotics #visualsimulation

AGIBOT

28,219 görüntüleme • 6 ay önce

🔥 JUST IN: Open-source robotics dataset from 100% real-world scenarios! 🤯 Chinese robotics company AGIBOT just released AGIBOT WORLD 2026, an open-source dataset systematically covering key embodied AI research directions. Built entirely from real-world environments: commercial spaces, and homes. Collected using AGIBOT G2 robots in free-form collection mode, providing structured, accurately annotated, high-quality data. Digital twin technology creates 1:1 scale replicas in simulation matching the real environments. Both real-world and simulation data are open-sourced. The AGIBOT G2 platform collects multiple data types simultaneously: RGB(D) cameras, tactile sensors, force sensors, LiDAR, IMU, and full-body joint states. Whole-body control coordinates arms, waist, and hands for complex tasks. First-person teleoperation lets operators control the robot from its perspective. The tasks covered are fine-grained manipulation, ultra-long-horizon tasks, spatial navigation, dual-arm coordination, and multi-agent/human-robot collaboration. The dataset includes error-recovery trajectories with annotations. Most datasets only show successful demonstrations. AGIBOT includes failures and how the robot recovers, teaching models how to handle mistakes. After collection, data is tested through policy training and real-robot deployment to ensure quality. Then processed through industrial quality control with multiple screening and cleaning rounds. Making it open-source accelerates embodied AI research by giving researchers access to high-quality real-world robot data at scale. 🇨🇳 Learn more here: ~~ ♻️ Join the weekly robotics newsletter, and never miss any news →
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🔥 JUST IN: Open-source robotics dataset from 100% real-world scenarios! 🤯 Chinese robotics company AGIBOT just released AGIBOT WORLD 2026, an open-source dataset systematically covering key embodied AI research directions. Built entirely from real-world environments: commercial spaces, and homes. Collected using AGIBOT G2 robots in free-form collection mode, providing structured, accurately annotated, high-quality data. Digital twin technology creates 1:1 scale replicas in simulation matching the real environments. Both real-world and simulation data are open-sourced. The AGIBOT G2 platform collects multiple data types simultaneously: RGB(D) cameras, tactile sensors, force sensors, LiDAR, IMU, and full-body joint states. Whole-body control coordinates arms, waist, and hands for complex tasks. First-person teleoperation lets operators control the robot from its perspective. The tasks covered are fine-grained manipulation, ultra-long-horizon tasks, spatial navigation, dual-arm coordination, and multi-agent/human-robot collaboration. The dataset includes error-recovery trajectories with annotations. Most datasets only show successful demonstrations. AGIBOT includes failures and how the robot recovers, teaching models how to handle mistakes. After collection, data is tested through policy training and real-robot deployment to ensure quality. Then processed through industrial quality control with multiple screening and cleaning rounds. Making it open-source accelerates embodied AI research by giving researchers access to high-quality real-world robot data at scale. 🇨🇳 Learn more here: ~~ ♻️ Join the weekly robotics newsletter, and never miss any news →

Lukas Ziegler

40,583 görüntüleme • 6 ay önce

Unitree G1 Open Source Dataset In order to promote the development of the global embodied AI industry, the Unitree G1 robot operation data set is open sourced, adapted to a variety of open source solutions, and continuously updated: Open source data collection: Open source learning algorithms: Open source datasets and models: #AI #Teleoperation #OpenSourceDataset #Unitree #EmbodiedAI #Humanoid #DataCollection #AGI
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Unitree G1 Open Source Dataset In order to promote the development of the global embodied AI industry, the Unitree G1 robot operation data set is open sourced, adapted to a variety of open source solutions, and continuously updated: Open source data collection: Open source learning algorithms: Open source datasets and models: #AI #Teleoperation #OpenSourceDataset #Unitree #EmbodiedAI #Humanoid #DataCollection #AGI

Unitree

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The industry's first embodied AI IDE, Booster Studio, is officially live at Built exclusively for embodied AI, Booster Studio integrates code editing, high-precision simulation, real-robot debugging, and real-world deployment into a single platform. Experience a true one-stop journey from your first idea to final hardware deployment. With its high-fidelity simulation environment and comprehensive development stack, Booster Studio shatters the barrier between digital and physical, bringing embodied AI to life. #boosterrobotics #embodiedai
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The industry's first embodied AI IDE, Booster Studio, is officially live at Built exclusively for embodied AI, Booster Studio integrates code editing, high-precision simulation, real-robot debugging, and real-world deployment into a single platform. Experience a true one-stop journey from your first idea to final hardware deployment. With its high-fidelity simulation environment and comprehensive development stack, Booster Studio shatters the barrier between digital and physical, bringing embodied AI to life. #boosterrobotics #embodiedai

Booster Robotics

597,241 görüntüleme • 4 ay önce

Real → Sim → Robot — fast. With Gaussian splats, GRID brings physical assets into simulation tools like AirGen and NVIDIA Isaac Sim, enabling AI skills to be tested in sim and deployed to real robots in minutes. #Robotics #PhysicalAI #Simulation
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Real → Sim → Robot — fast. With Gaussian splats, GRID brings physical assets into simulation tools like AirGen and NVIDIA Isaac Sim, enabling AI skills to be tested in sim and deployed to real robots in minutes. #Robotics #PhysicalAI #Simulation

General Robotics

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#AGIBOTAIWeek Day 3: Introducing GO-2: the next-generation foundation model for embodied AI, built to unify reasoning and action. To truly bridge “thinking” and “doing,” embodied AI must solve two challenges at once: • It generate executable action plans through deep spatial reasoning • It deliver stable execution in real-world environments GO-2 tackles both with a comprehensive architecture: Action Chain-of-Thought for action reasoning, and an Asynchronous Dual-System for robust execution. #AGIBOT #AGIBOTAIWeek #Foundation #model #EmbodiedAI Official account tags X: AGIBOT LinkedIn: agibot
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#AGIBOTAIWeek Day 3: Introducing GO-2: the next-generation foundation model for embodied AI, built to unify reasoning and action. To truly bridge “thinking” and “doing,” embodied AI must solve two challenges at once: • It generate executable action plans through deep spatial reasoning • It deliver stable execution in real-world environments GO-2 tackles both with a comprehensive architecture: Action Chain-of-Thought for action reasoning, and an Asynchronous Dual-System for robust execution. #AGIBOT #AGIBOTAIWeek #Foundation #model #EmbodiedAI Official account tags X: AGIBOT LinkedIn: agibot

Hasan Toor

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Before AI can understand the physical world, it needs data about the physical world. Not just images. Spatial environments. Real streets, buildings, parks, stores, museums, and public spaces captured in 3D. OVER has already reconstructed 290,000+ real-world 3D scenes, creating a growing dataset for the next generation of spatial and embodied AI. And this is exactly the kind of real-world spatial data AI companies are looking for. We're already in conversations with multiple AI and Robotics companies exploring how OVER's dataset can support the development and training of models that need to understand the physical world. The next AI race will be about real-world data.
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Before AI can understand the physical world, it needs data about the physical world. Not just images. Spatial environments. Real streets, buildings, parks, stores, museums, and public spaces captured in 3D. OVER has already reconstructed 290,000+ real-world 3D scenes, creating a growing dataset for the next generation of spatial and embodied AI. And this is exactly the kind of real-world spatial data AI companies are looking for. We're already in conversations with multiple AI and Robotics companies exploring how OVER's dataset can support the development and training of models that need to understand the physical world. The next AI race will be about real-world data.

Over the Reality 🌐

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From a single image to a full robotics simulation. 360 image → Marble → 3D environment → Robotics sim This is how we scale world creation for embodied AI with Lightwheel, turning lightweight capture into simulation-ready environments in minutes, not weeks.
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From a single image to a full robotics simulation. 360 image → Marble → 3D environment → Robotics sim This is how we scale world creation for embodied AI with Lightwheel, turning lightweight capture into simulation-ready environments in minutes, not weeks.

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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
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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

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We built a fully open-source dexterous robotic hand — for just $314. 🤖 Meet Aero Hand Open — precise, affordable, and built for embodied AI research. Watch it perform natural finger motions 👇 🔗 📘 Docs: 💻 GitHub: #robotics #opensource #AI #dexteroushand #embodiedAI
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We built a fully open-source dexterous robotic hand — for just $314. 🤖 Meet Aero Hand Open — precise, affordable, and built for embodied AI research. Watch it perform natural finger motions 👇 🔗 📘 Docs: 💻 GitHub: #robotics #opensource #AI #dexteroushand #embodiedAI

Chestnut Robotics

58,061 görüntüleme • 1 yıl önce

Researchers are using Marble to generate simulation-ready robotics environments (scenes + collider meshes) then bring them into NVIDIA Robotics Isaac Sim for training + evaluation without any manual environment setup. Case Study:
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Researchers are using Marble to generate simulation-ready robotics environments (scenes + collider meshes) then bring them into NVIDIA Robotics Isaac Sim for training + evaluation without any manual environment setup. Case Study:

World Labs

29,857 görüntüleme • 10 ay önce

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.
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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.

CyberRobo

17,092 görüntüleme • 5 ay önce

🚀 MiniCPM enters the physical world — enabling robots to understand, remember, and act. We open-source MiniCPM-Robot, our first embodied AI model series, including: 🤖 MiniCPM-RobotManip — a 1.5B general-purpose Vision-Language-Action (VLA) model for robotic manipulation. 🐕 MiniCPM-RobotTrack — a compact model for real-world target tracking. ⚡ PhyAI — a high-performance inference framework built for embodied models. Together, they bring efficient, practical, and open embodied intelligence closer to real-world robots. ⭐ GitHub: 🤗 MiniCPM-RobotManip: 🤗 MiniCPM-RobotTrack:
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🚀 MiniCPM enters the physical world — enabling robots to understand, remember, and act. We open-source MiniCPM-Robot, our first embodied AI model series, including: 🤖 MiniCPM-RobotManip — a 1.5B general-purpose Vision-Language-Action (VLA) model for robotic manipulation. 🐕 MiniCPM-RobotTrack — a compact model for real-world target tracking. ⚡ PhyAI — a high-performance inference framework built for embodied models. Together, they bring efficient, practical, and open embodied intelligence closer to real-world robots. ⭐ GitHub: 🤗 MiniCPM-RobotManip: 🤗 MiniCPM-RobotTrack:

OpenBMB

332,156 görüntüleme • 3 ay önce

The wait is over. Meet the reBot-DevArm B601—the fully open-source robotic arm. 🦾 Built, broken, and rebuilt for reliability. Here’s what makes it unique: ✅ 1.5kg payload & 650mm reach ✅ 6+1 DOF for complex tasks ✅ Plug-and-play with ROS2, Isaac Sim, LeRobot We tested it endlessly—7x24h runs, overload tests, gravity compensation—to make it a robust platform for embodied AI. And it’s 100% open-source (BOM, CAD, code). Build, hack, and innovate. All files & tutorials are live on GitHub. Check it out and join the build! 🔗Explore the GitHub here:
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The wait is over. Meet the reBot-DevArm B601—the fully open-source robotic arm. 🦾 Built, broken, and rebuilt for reliability. Here’s what makes it unique: ✅ 1.5kg payload & 650mm reach ✅ 6+1 DOF for complex tasks ✅ Plug-and-play with ROS2, Isaac Sim, LeRobot We tested it endlessly—7x24h runs, overload tests, gravity compensation—to make it a robust platform for embodied AI. And it’s 100% open-source (BOM, CAD, code). Build, hack, and innovate. All files & tutorials are live on GitHub. Check it out and join the build! 🔗Explore the GitHub here:

Seeed Studio

29,412 görüntüleme • 7 ay önce

How do we make robot policy evaluation reproducible across labs? Announcing OpenArm 02: a fully open-source dual arm platform, with a unified setup for reproducible evaluation: controlled tasks, backgrounds, lighting, and camera angles. ✅ Fully open-source, so anyone can replicate the setup anywhere ✅ AutoEval: 24/7 real-world evaluation with minimal human intervention (building on work by Paul Zhou) ✅ Fair side-by-side policy comparison OpenArm is the open foundation to turn isolated results into shared progress. Releasing soon. Stay tuned.
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How do we make robot policy evaluation reproducible across labs? Announcing OpenArm 02: a fully open-source dual arm platform, with a unified setup for reproducible evaluation: controlled tasks, backgrounds, lighting, and camera angles. ✅ Fully open-source, so anyone can replicate the setup anywhere ✅ AutoEval: 24/7 real-world evaluation with minimal human intervention (building on work by Paul Zhou) ✅ Fair side-by-side policy comparison OpenArm is the open foundation to turn isolated results into shared progress. Releasing soon. Stay tuned.

Enactic

65,684 görüntüleme • 7 ay önce

Hours of manual asset authoring => Down to 1–2 minutes with 1 prompt. SR Platform generates interactive, simulation-ready 3D assets for training robotics, complete with articulated objects and physics. Native support for MuJoCo and NVIDIA Isaac Sim. Coming in July!
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Hours of manual asset authoring => Down to 1–2 minutes with 1 prompt. SR Platform generates interactive, simulation-ready 3D assets for training robotics, complete with articulated objects and physics. Native support for MuJoCo and NVIDIA Isaac Sim. Coming in July!

Strike Robot

12,942 görüntüleme • 3 ay önce

One month after launching SR Platform. We started with simple simulation assets and layouts. Today, thanks to continuous improvements, SR Platform generates environments with richer geometry, higher-fidelity surface materials, and significantly more realistic assets, ready for modern robotics simulation. Most importantly, SR Platform is now fully compatible with NVIDIA Robotics Isaac Sim. Built with: • Agentic workflow & tool calling • Dynamic context retrieval • Self-evaluation & iterative refinement • Latest GPT-5.6 model variants
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One month after launching SR Platform. We started with simple simulation assets and layouts. Today, thanks to continuous improvements, SR Platform generates environments with richer geometry, higher-fidelity surface materials, and significantly more realistic assets, ready for modern robotics simulation. Most importantly, SR Platform is now fully compatible with NVIDIA Robotics Isaac Sim. Built with: • Agentic workflow & tool calling • Dynamic context retrieval • Self-evaluation & iterative refinement • Latest GPT-5.6 model variants

Strike Robot

15,277 görüntüleme • 3 ay önce