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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 просмотров • 9 месяцев назад •via X (Twitter)

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Комментарии: 4

Фото профиля The AI Index
The AI Index9 месяцев назад

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

Фото профиля Himanshu Kumar
Himanshu Kumar9 месяцев назад

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

Фото профиля Angel
Angel9 месяцев назад

thank you!

Фото профиля Nikhil Deshpande
Nikhil Deshpande9 месяцев назад

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.

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28,219 просмотров • 6 месяцев назад

🔥 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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332,156 просмотров • 3 месяцев назад

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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.

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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!
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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 просмотров • 3 месяцев назад

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