.. IR-SIM documentation master file, created by sphinx-quickstart on Tue Aug 6 00:59:39 2024. You can adapt this file completely to your liking, but it should at least contain the root `toctree` directive. ================================== Welcome to IR-SIM's documentation! ================================== **IR-SIM** is an open-source, Python-based, lightweight robot simulator designed for navigation, control, and learning. It provides a simple, user-friendly framework with built-in collision detection for modeling robots, sensors, and environments. Ideal for academic and educational use, IR-SIM enables rapid prototyping of robotics and AI algorithms in custom scenarios with minimal coding and hardware requirements. .. grid:: 1 2 2 2 :gutter: 2 .. grid-item-card:: 🚀 Quick Start :link: get_started/index :link-type: doc :text-align: center Get up and running with IR-SIM in minutes .. grid-item-card:: 📚 User Guide :link: usage/index :link-type: doc :text-align: center Learn how to use IR-SIM effectively .. grid-item-card:: ⚙️ Configuration :link: yaml_config/index :link-type: doc :text-align: center YAML configuration syntax and examples .. grid-item-card:: 🔧 API Reference :link: api/index :link-type: doc :text-align: center Complete API documentation .. grid-item-card:: 📋 Changelog :link: changelog :link-type: doc :text-align: center Version history and release notes .. grid-item-card:: 🤝 Contributing :link: contributing :link-type: doc :text-align: center Guide for contributors ---- Key Features ================= - Simulate a wide range of robot platforms with diverse kinematics, sensors, and behaviors - Quickly configure and customize simulation scenarios using straightforward YAML files, with no complex coding required - Visualize simulation outcomes in real time for immediate feedback and analysis using matplotlib - Support collision detection and behavior control for each object in the simulation .. grid:: 3 3 3 3 .. grid-item-card:: :shadow: lg :text-align: center .. image:: https://github.com/user-attachments/assets/5930b088-d400-4943-8ded-853c22eae75b :width: 70% :alt: Multi-robot collision avoidance +++ Multi-robot collision avoidance .. grid-item-card:: :shadow: lg :text-align: center .. image:: https://github.com/user-attachments/assets/3257abc1-8bed-40d8-9b51-e5d90b06ee06 :width: 70% :alt: Navigation in Grid World +++ Navigation in Grid World .. grid-item-card:: :shadow: lg :text-align: center .. image:: https://github.com/user-attachments/assets/7aa809c2-3a44-4377-a22d-728b9dbdf8bc :width: 70% :alt: Sensor visualization +++ Sensor visualization .. grid-item-card:: :shadow: lg :text-align: center .. image:: https://github.com/user-attachments/assets/1cc8a4a6-2f41-4bc9-bc59-a7faff443223 :width: 70% :alt: Dynamic environment simulation +++ Dynamic environment simulation .. grid-item-card:: :shadow: lg :text-align: center .. image:: https://github.com/user-attachments/assets/0fac81e7-60c0-46b2-91f0-efe4762bb758 :width: 70% :alt: 3D habitat spaces +++ 3D habitat spaces .. grid-item-card:: :shadow: lg :text-align: center .. image:: usage/gif/mouse.gif :width: 70% :alt: Mouse control +++ Mouse control ---- .. toctree:: :maxdepth: 2 :caption: Documentation :hidden: Getting Started User Guide Configuration API Reference .. toctree:: :maxdepth: 2 :caption: Development :hidden: Contributing Changelog ---- Get Started =============== Ready to start using IR-SIM? Choose your preferred installation method: .. grid:: 1 3 3 3 .. grid-item-card:: 📦 pip :link: get_started/install :link-type: doc :text-align: center :shadow: md :bdg-success:`Recommended` ^^^ Quick installation with pip .. grid-item-card:: 🐍 conda :link: get_started/install :link-type: doc :text-align: center :shadow: md :bdg-info:`Popular` ^^^ Installation in conda environment .. grid-item-card:: ⚡ uv :link: get_started/install :link-type: doc :text-align: center :shadow: md :bdg-warning:`Fast` ^^^ Lightning-fast installation ---- Projects using IR-SIM ======================== .. grid:: 1 1 1 1 .. grid-item-card:: Academic projects :shadow: md * `rl-rvo-nav (RAL & ICRA2023) `_ * `RDA_planner (RAL & IROS2023) `_ * `NeuPAN (T-RO 2025) `_ .. grid-item-card:: Deep Reinforcement Learning Projects :shadow: md * `DRL-robot-navigation-IR-SIM `_ * `AutoNavRL `_