{"id":22606,"url":"https://github.com/simjaecheol/awesome-simulation","name":"awesome-simulation","description":"simulations for reinforcement learning","projects_count":47,"last_synced_at":"2026-06-03T00:00:27.340Z","repository":{"id":138063097,"uuid":"432404317","full_name":"simjaecheol/awesome-simulation","owner":"simjaecheol","description":"simulations for reinforcement learning","archived":false,"fork":false,"pushed_at":"2022-02-02T07:09:20.000Z","size":18,"stargazers_count":1,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2026-05-17T11:03:34.799Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":null,"language":null,"has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"other","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/simjaecheol.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":".github/CODEOWNERS","security":null,"support":null,"governance":null,"roadmap":null,"authors":null}},"created_at":"2021-11-27T08:10:24.000Z","updated_at":"2022-10-20T10:59:27.000Z","dependencies_parsed_at":"2024-01-15T20:46:57.037Z","dependency_job_id":"1bd0eb2a-55c8-4f07-8dac-3d0c6217c05e","html_url":"https://github.com/simjaecheol/awesome-simulation","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/simjaecheol/awesome-simulation","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/simjaecheol%2Fawesome-simulation","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/simjaecheol%2Fawesome-simulation/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/simjaecheol%2Fawesome-simulation/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/simjaecheol%2Fawesome-simulation/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/simjaecheol","download_url":"https://codeload.github.com/simjaecheol/awesome-simulation/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/simjaecheol%2Fawesome-simulation/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":33841996,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-05-26T15:22:16.424Z","status":"online","status_checked_at":"2026-06-02T02:00:07.132Z","response_time":109,"last_error":null,"robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":true,"can_crawl_api":true,"host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"created_at":"2024-01-13T12:56:21.573Z","updated_at":"2026-06-03T00:00:27.341Z","primary_language":null,"list_of_lists":false,"displayable":true,"categories":["[PyBullet](https://github.com/bulletphysics/bullet3)","[NVIDIA-Omniverse](https://developer.nvidia.com/nvidia-omniverse-platform)","[MuJoCo](https://mujoco.org)","[Unreal Engine](https://www.unrealengine.com/en-US/)","[Open AI Gym](https://gym.openai.com/)","[Unity](https://unity.com/)","[Brax](https://arxiv.org/abs/2106.13281)","[Gazebo](http://gazebosim.org/)","[nvisii](https://nvisii.com/)"],"sub_categories":[],"readme":"# Awesome Simulation [![Awesome](https://cdn.rawgit.com/sindresorhus/awesome/d7305f38d29fed78fa85652e3a63e154dd8e8829/media/badge.svg)](https://github.com/sindresorhus/awesome)\n\nA curated list of awesome simulation frameworks and projects\n\n\n- [Awesome Simulation](#awesome-simulation)\n    - [PyBullet](#PyBullet)\n    - [MuJoCo](#MuJoCo)\n    - [Gazebo](#Gazebo)\n    - [Brax](#Brax)\n    - [NVIDIA-Omniverse](#NVIDIA-Omniverse)\n    - [Unreal Engine](#Unreal-Engine)\n    - [Unity](#Unity)\n\n- [Reinforcement Learning Toolkit](#Reinforcement-Learning-Platform)\n    - [Open AI Gym](#Open-AI-Gym)\n    - [MLAgent](#ml-agents)\n\n- [Renderer](#Renderer)\n    - [NVIDIA/nvisii](#nvisii)\n\n- [Contributing](#contributing)\n\n---\n\n## [PyBullet](https://github.com/bulletphysics/bullet3)\n\n[Github](https://github.com/bulletphysics/bullet3)\n\n[Guide](https://docs.google.com/document/d/10sXEhzFRSnvFcl3XxNGhnD4N2SedqwdAvK3dsihxVUA/edit#heading=h.2ye70wns7io3)\n\nLicense: zlib license\n\nLanguages: python 3\n\nPhysics Engine: bullet\n\n* [pybullet-gym](https://github.com/benelot/pybullet-gym) - Open-source implementation of OpenAI Gym MuJoCo environments for use with the OpenAI Gym Reinforcement Learning Research Platform\n* [pybullet_robots](https://github.com/erwincoumans/pybullet_robots) - Prototyping robots for PyBullet\n* [ravens](https://github.com/google-research/ravens) - Train robotic agents to learn pick and place with deep learning for vision-based manipulation in PyBullet. Transporter Nets, CoRL 2020.\n* [gym-pybullet-drones](https://github.com/utiasDSL/gym-pybullet-drones) - PyBullet Gym environments for single and multi-agent reinforcement learning of quadcopter control\n* [pybullet-planning](https://github.com/caelan/pybullet-planning) - PyBullet Planning\n* [pybullet_planning](https://github.com/yijiangh/pybullet_planning) - A suite of utility functions to facilitate robotic planning related research on the pybullet physics simulation engine.\n* [pybullet-robot-envs](https://github.com/robotology-playground/pybullet-robot-envs)\n* [pybullet_rendering](https://github.com/ikalevatykh/pybullet_rendering) - External rendering for PyBullet\n* [quadruped_ctrl](https://github.com/Derek-TH-Wang/quadruped_ctrl) - MIT mini cheetah quadruped robot simulated in pybullet environment using ros.\n* [panda-gym](https://github.com/qgallouedec/panda-gym) - OpenaAI Gym Franka Emika Panda robot environment based on PyBullet.\n* [pybullet_multigoal_gym](https://github.com/IanYangChina/pybullet_multigoal_gym) - Pybullet version of the multigoal robotics environment from OpenAI Gym\n\n## [MuJoCo](https://mujoco.org)\n\n[Github](https://github.com/deepmind/mujoco)\n\n[Documents](https://mujoco.readthedocs.io/en/latest/overview.html)\n\nLicense: Apache License 2.0\n\nLanguages: C\n\nPhysics Engine: MuJoCo\n\n* [dm_control](https://github.com/deepmind/dm_control) - DeepMind's software stack for physics-based simulation\n* [mujoco-py](https://github.com/openai/mujoco-py) - mujoco-py allows using MuJoCo from Python 3\n* [mujoco-worldgen](https://github.com/openai/mujoco-worldgen) - Automatic object XML generation for Mujoco\n* [mjrl](https://github.com/aravindr93/mjrl) - Reinforcement learning algorithms for MuJoCo tasks\n* [multiagent_mujoco](https://github.com/schroederdewitt/multiagent_mujoco) - Benchmark for Continuous Multi Agent Robotic Control, based on OpenAI's Mujoco Gym environments\n* [metaworld](https://github.com/rlworkgroup/metaworld) - An open source robotics benchmark for meta- and multi-task reinforcement learning\n* [cassie-mujoco-sim](https://github.com/osudrl/cassie-mujoco-sim) - A simulation library for Agility Robotics' Cassie robot using MuJoCo\n* [MuJoCo_RL_UR5](https://github.com/PaulDanielML/MuJoCo_RL_UR5) - A MuJoCo/Gym environment for robot control using Reinforcement Learning. The task of agents in this environment is pixel-wise prediction of grasp success chances.\n\n## [Gazebo](http://gazebosim.org/)\n\n[Github](https://github.com/osrf/gazebo)\n\nLicense: Apache License 2.0\n\nSupport Languagues: C++, Python\n\nPhysics: ODE, Bullet, Simbody and DART\n\n* [osrf/gazebo_tutorials](https://github.com/osrf/gazebo_tutorials) - Tutorials for gazebo\n* [ros-simulation/gazebo_ros_pkgs](https://github.com/ros-simulation/gazebo_ros_pkgs) - Wrappers, tools and additional API's for using ROS with Gazebo\n* [osrf/gazebo_models](https://github.com/osrf/gazebo_models) - Model database\n* [PX4/PX4-SITL_gazebo](https://github.com/PX4/PX4-SITL_gazebo) - Set of plugins, models and worlds to use with OSRF Gazebo Simulator in SITL and HITL.\n* [robin-shaun/XTDrone](https://github.com/robin-shaun/XTDrone) - UAV Simulation Platform based on PX4, ROS and Gazebo\n* [ethz-asl/rotors_simulator](https://github.com/ethz-asl/rotors_simulator) - RotorS is a UAV gazebo simulator\n* [lihuang3/ur5_ROS-Gazebo](https://github.com/lihuang3/ur5_ROS-Gazebo) - Universal Robot (UR5) Pick and Place Simulation in ROS-Gazebo with a USB Cam and Vacuum Grippers\n* [ignitionrobotics/ign-gazebo](https://github.com/ignitionrobotics/ign-gazebo) - Open source robotics simulator. Through Ignition Gazebo users have access to high fidelity physics, rendering, and sensor models.\n* [turtlebot/turtlebot_simulator](https://github.com/turtlebot/turtlebot_simulator) - Launcers for Gazebo simulation of the TurtleBot\n* [mit-racecar/racecar_gazebo](https://github.com/mit-racecar/racecar_gazebo) - A gazebo-based simulator of the MIT Racecar.\n* [fkromer/awesome-gazebo](https://github.com/fkromer/awesome-gazebo) - Gazebo, the simulation framework for ROS1 and ROS2 is awesome!\n\n## [Brax](https://arxiv.org/abs/2106.13281)\n\n[Github](https://github.com/google/brax)\n\nLicense: Apache 2.0\n\nSupport Languages: Python\n\n## [NVIDIA-Omniverse](https://developer.nvidia.com/nvidia-omniverse-platform)\n\nPhysics: PhysicsX\n\n* [IsaacSim](https://developer.nvidia.com/isaac-sim)\n\n* [IsaacGym](https://developer.nvidia.com/isaac-gym)\n\n* [IsaacGymEnvs](https://github.com/NVIDIA-Omniverse/IsaacGymEnvs)\n\n\n## [Unreal Engine](https://www.unrealengine.com/en-US/)\n\n[Github](https://github.com/EpicGames/UnrealEngine)\n\nTo access this repository, you have to get permission from epic games\n\n[Documentation](https://docs.unrealengine.com/4.27/en-US/)\n\nLicense: Unreal Engine\n\nSupport Languages: C++\n\nPhysics Engine: PhyX\n\n* [UnrealEnginePython](https://github.com/20tab/UnrealEnginePython) - Embed Python in Unreal Engine 4\n* [UnrealCV](https://github.com/unrealcv/unrealcv) - Connecting Computer Vision to Unreal Engine\n* [Carla](https://github.com/carla-simulator/carla) - Open-source simulator for autonomous driving research.\n\n## [Unity](https://unity.com/)\n\n* [LG SVL Simulator](https://github.com/lgsvl/simulator) - A ROS/ROS2 Multi-robot Simulator for Autonomous Vehicles\n\n\n# Reinforcement Learning Toolkit\n\n## [Open AI Gym](https://gym.openai.com/)\n\n[Github](https://github.com/openai/gym) - A toolkit for developing and comparing reinforcement learning algorithms.\n\nLicense: MIT License\n\nLanguage: Python\n\n## [ml-agents](https://github.com/Unity-Technologies/ml-agents)\n\nLicense: Apache 2.0\n\nLanguage: C#, Python\n\n# Renderer\n\n## [nvisii](https://nvisii.com/)\n\n[Github](https://github.com/owl-project/NVISII) - A python-enabled ray tracing based renderer built on top of NVIDIA OptiX (C++/CUDA backend).\n\nLICENSE: Apache 2.0\n\nLaunguage: C, C++\n\n\n# Contributing\n\nYour contributions are always welcome!\n","projects_url":"https://awesome.ecosyste.ms/api/v1/lists/simjaecheol%2Fawesome-simulation/projects"}