ИИ-агенты
IsaacLab
Isaac Lab — NVIDIA's unified framework for robot learning, with 30+ environments and multi-physics simulation.
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Смотреть руководство →genesis-world — проект с открытым исходным кодом из категории «ИИ-агенты» от Genesis-Embodied-AI (Genesis-Embodied-AI/genesis-world на GitHub). У него 30 035 звёзд на GitHub и 2 878 форков, он распространяется по лицензии Apache-2.0 и последний раз обновлялся на GitHub 8 октября 2026.
A Python simulation platform for robotics and embodied AI — fast physics, rendering and learning
Decide what you want to achieve with genesis-world and check the README on GitHub for requirements before installing.
Clone the repository from GitHub (or take the packaged install route in step 3 if the README offers one).
Follow the project's documented install commands — the Run section below lists the exact ones — and add any required API keys or models.
Work through the README's quickstart example end to end, then adapt it to your own project or data.
A catalogue of solvers for rigid bodies, fluids, soft bodies and more, per the README's physics catalogue.
Rendering options for visualizing simulations and generating training imagery.
A clean Python API for building scenes, adding robots and stepping the simulation.
Installable extras add solvers and renderers (for example pyuipc for the IPC solver, gs-nyx for the Nyx renderer).
Documented install paths for NVIDIA CUDA, CPU-only and Apple Silicon (Metal/MPS) via uv/PyTorch builds.
Ships with citation info and is used as a platform for embodied-AI learning research.
Get the Genesis source for the development/editable route; most users pip-install instead.
git clone https://github.com/Genesis-Embodied-AI/genesis-world.git
cd genesis-worldInstall the released package (requires Python >=3.10, <3.14).
pip install genesis-worldFollow the documentation quickstart to create a scene, add a robot and step the simulation in Python.
# see https://genesis-world.readthedocs.io for the first-scene example codegenesis-world is maintained by the Genesis-Embodied-AI organization/account on GitHub, together with open-source contributors, in the public repository Genesis-Embodied-AI/genesis-world.
Yes — the code is open source under the Apache-2.0 license. You can use, modify and redistribute it under that license's terms.
No API key — Genesis is a local simulation platform. You need suitable hardware (an NVIDIA GPU is recommended for larger scenes) and PyTorch.
Genesis aims for a unified, Pythonic platform spanning many physics types and renderers, positioning itself as an accessible all-in-one alternative to single-purpose simulators.
Clone the repository from GitHub, follow the install commands in the Run section (taken from the project's README), and complete the documented quickstart example before adapting it to your own use case.
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