genesis-world
A Python simulation platform for robotics and embodied AI — fast physics, rendering and learning
IsaacLab é um projeto de agentes de IA de código aberto de isaac-sim (isaac-sim/IsaacLab no GitHub). Tem 8.299 estrelas no GitHub e 3.940 forks, é publicado sob a licença BSD-3-Clause e foi atualizado pela última vez no GitHub em 8 de outubro de 2026.
Isaac Lab — NVIDIA's unified framework for robot learning, with 30+ environments and multi-physics simulation.
Confirm your Isaac Sim version matches the Isaac Lab release, and pick a robot and environment that match your learning problem.
Clone isaac-sim/IsaacLab from GitHub (or use the install path in the run steps below) and skim its README for the parts relevant to your goal.
Install Isaac Sim first, then install Isaac Lab following the official documentation for your Isaac Sim version.
Launch one of the ready-to-train environments, run a short training pass with your chosen RL framework, and view the robot in the simulator.
A diverse collection from manipulators and quadrupeds to humanoids, ready to drop into learning environments.
Implementations you can train directly with RSL RL, SKRL, RL Games or Stable Baselines, including multi-agent RL support.
Rigid bodies, articulated systems and deformable objects, so contact-rich tasks can be modelled.
RGB, depth and segmentation cameras with annotations, IMU, contact sensors and ray casters for perception-driven policies.
Runs as part of the Isaac Sim / Omniverse ecosystem, with multi-physics and multi-renderer support.
The project publishes a performance dashboard so you can gauge throughput for environments before committing hardware.
Get the source from the official GitHub repository for IsaacLab.
git clone https://github.com/isaac-sim/IsaacLab.git
cd IsaacLabInstall Isaac Sim for your platform, then follow the Isaac Lab installation documentation matched to that Isaac Sim version.
# Install Isaac Sim first, then Isaac Lab per https://isaac-sim.github.io/IsaacLab — see READMEPick a ready-to-train environment and start training with one of the supported RL frameworks, following the docs' getting-started guide.
# Launch a documented training example for your chosen environment and RL framework — see README docsThe isaac-sim project (NVIDIA's Isaac Sim ecosystem), through the isaac-sim/IsaacLab repository, with docs at isaac-sim.github.io/IsaacLab.
Yes — the project is open source under the BSD-3-Clause license as recorded for this listing. See the license terms for any conditions on redistribution.
Isaac Lab is free and BSD-3-Clause licensed, but it requires NVIDIA Isaac Sim and suitable GPU hardware; there is no API key, though Isaac Sim has its own install and system requirements.
A general simulator makes you build robots, environments and sensor plumbing yourself. Isaac Lab ships the robots, 30+ environments and RL-framework wiring on top of Isaac Sim — you start from training, at the cost of living in NVIDIA's ecosystem.
Clone the repository (or use the documented installer), follow the install and configure steps on this page, and run the smallest real task first — launch one of the ready-to-train environments, run a short training pass with your chosen RL framework, and view the robot in the simulator.
A Python simulation platform for robotics and embodied AI — fast physics, rendering and learning
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Grátis e aberto: pegue o código-fonte, dê uma estrela no repositório e comece a criar.