KI-Agenten
IsaacLab
Isaac Lab — NVIDIA's unified framework for robot learning, with 30+ environments and multi-physics simulation.
★ 8,3 Tsd. SterneBSD-3-Clause
Anleitung ansehen →genesis-world ist ein Open-Source-Projekt aus der Kategorie KI-Agenten von Genesis-Embodied-AI (Genesis-Embodied-AI/genesis-world auf GitHub). Es hat 30.035 Sterne auf GitHub und 2.878 Forks, wird unter der Lizenz Apache-2.0 veröffentlicht und wurde zuletzt am 8. Oktober 2026 auf GitHub aktualisiert.
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.
Isaac Lab — NVIDIA's unified framework for robot learning, with 30+ environments and multi-physics simulation.
Hugging Face's LeRobot: datasets, models and tools to make real-world robotics AI accessible
Voyager — the open-ended embodied Minecraft agent that writes its own skills and keeps learning for life.
Python library for building multimodal language agents — VLM, video and mobile, fast to prototype and ship
The official Python SDK for building on Vapi's voice AI platform.
Google's Python SDK for building AI agents on the Antigravity platform and Gemini models.
Die anderen Projekte der Kategorie KI-Agenten mit den meisten Sternen im LibreAI-Katalog — die realistische Auswahl, falls genesis-world nicht das Richtige ist.
A personal AI that really does things — on any OS, with your data staying yours.
An agentic skills framework & software development methodology that works.
Agent harness optimization system with skills, memory and security for Claude Code, Codex and more
The agent that grows with you — a Python framework for adaptive AI agents.
DeepSeek's plugin-based agent harness where everything is a plugin.
Verwandte Projekte der Kategorie KI-Agenten im Katalog, die genesis-world bei den Sternen am nächsten stehen — zum Weiterstöbern auf beiden Seiten.
Over a thousand tool integrations so agents can turn intent into action.
The batteries-included agent harness from the LangChain team.
A lightweight, container-isolated personal AI agent for WhatsApp, Telegram, Slack and more
An autonomous research agent that plans, searches and writes cited reports from any data source
The memory API that gives AI apps instant, lasting context.
smolagents — Hugging Face's barebones agent library where agents think in code: a CodeAgent that writes its actions as Python, model-agnostic, Apache-2.0
Kostenlos und offen — hol dir den Quellcode, gib dem Repository einen Stern und leg los.