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https://github.com/simjaecheol/awesome-simulation

simulations for reinforcement learning
https://github.com/simjaecheol/awesome-simulation

List: awesome-simulation

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simulations for reinforcement learning

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# Awesome Simulation [![Awesome](https://cdn.rawgit.com/sindresorhus/awesome/d7305f38d29fed78fa85652e3a63e154dd8e8829/media/badge.svg)](https://github.com/sindresorhus/awesome)



A curated list of awesome simulation frameworks and projects



- [Awesome Simulation](#awesome-simulation)

    - [PyBullet](#PyBullet)

    - [MuJoCo](#MuJoCo)

    - [Gazebo](#Gazebo)

    - [Brax](#Brax)

    - [NVIDIA-Omniverse](#NVIDIA-Omniverse)

    - [Unreal Engine](#Unreal-Engine)

    - [Unity](#Unity)



- [Reinforcement Learning Toolkit](#Reinforcement-Learning-Platform)

    - [Open AI Gym](#Open-AI-Gym)

    - [MLAgent](#ml-agents)



- [Renderer](#Renderer)

    - [NVIDIA/nvisii](#nvisii)



- [Contributing](#contributing)



---



## [PyBullet](https://github.com/bulletphysics/bullet3)



[Github](https://github.com/bulletphysics/bullet3)



[Guide](https://docs.google.com/document/d/10sXEhzFRSnvFcl3XxNGhnD4N2SedqwdAvK3dsihxVUA/edit#heading=h.2ye70wns7io3)



License: zlib license



Languages: python 3



Physics Engine: bullet



* [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

* [pybullet_robots](https://github.com/erwincoumans/pybullet_robots) - Prototyping robots for PyBullet

* [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.

* [gym-pybullet-drones](https://github.com/utiasDSL/gym-pybullet-drones) - PyBullet Gym environments for single and multi-agent reinforcement learning of quadcopter control

* [pybullet-planning](https://github.com/caelan/pybullet-planning) - PyBullet Planning

* [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.

* [pybullet-robot-envs](https://github.com/robotology-playground/pybullet-robot-envs)

* [pybullet_rendering](https://github.com/ikalevatykh/pybullet_rendering) - External rendering for PyBullet

* [quadruped_ctrl](https://github.com/Derek-TH-Wang/quadruped_ctrl) - MIT mini cheetah quadruped robot simulated in pybullet environment using ros.

* [panda-gym](https://github.com/qgallouedec/panda-gym) - OpenaAI Gym Franka Emika Panda robot environment based on PyBullet.

* [pybullet_multigoal_gym](https://github.com/IanYangChina/pybullet_multigoal_gym) - Pybullet version of the multigoal robotics environment from OpenAI Gym



## [MuJoCo](https://mujoco.org)



[Github](https://github.com/deepmind/mujoco)



[Documents](https://mujoco.readthedocs.io/en/latest/overview.html)



License: Apache License 2.0



Languages: C



Physics Engine: MuJoCo



* [dm_control](https://github.com/deepmind/dm_control) - DeepMind's software stack for physics-based simulation

* [mujoco-py](https://github.com/openai/mujoco-py) - mujoco-py allows using MuJoCo from Python 3

* [mujoco-worldgen](https://github.com/openai/mujoco-worldgen) - Automatic object XML generation for Mujoco

* [mjrl](https://github.com/aravindr93/mjrl) - Reinforcement learning algorithms for MuJoCo tasks

* [multiagent_mujoco](https://github.com/schroederdewitt/multiagent_mujoco) - Benchmark for Continuous Multi Agent Robotic Control, based on OpenAI's Mujoco Gym environments

* [metaworld](https://github.com/rlworkgroup/metaworld) - An open source robotics benchmark for meta- and multi-task reinforcement learning

* [cassie-mujoco-sim](https://github.com/osudrl/cassie-mujoco-sim) - A simulation library for Agility Robotics' Cassie robot using MuJoCo

* [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.



## [Gazebo](http://gazebosim.org/)



[Github](https://github.com/osrf/gazebo)



License: Apache License 2.0



Support Languagues: C++, Python



Physics: ODE, Bullet, Simbody and DART



* [osrf/gazebo_tutorials](https://github.com/osrf/gazebo_tutorials) - Tutorials for gazebo

* [ros-simulation/gazebo_ros_pkgs](https://github.com/ros-simulation/gazebo_ros_pkgs) - Wrappers, tools and additional API's for using ROS with Gazebo

* [osrf/gazebo_models](https://github.com/osrf/gazebo_models) - Model database

* [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.

* [robin-shaun/XTDrone](https://github.com/robin-shaun/XTDrone) - UAV Simulation Platform based on PX4, ROS and Gazebo

* [ethz-asl/rotors_simulator](https://github.com/ethz-asl/rotors_simulator) - RotorS is a UAV gazebo simulator

* [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

* [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.

* [turtlebot/turtlebot_simulator](https://github.com/turtlebot/turtlebot_simulator) - Launcers for Gazebo simulation of the TurtleBot

* [mit-racecar/racecar_gazebo](https://github.com/mit-racecar/racecar_gazebo) - A gazebo-based simulator of the MIT Racecar.

* [fkromer/awesome-gazebo](https://github.com/fkromer/awesome-gazebo) - Gazebo, the simulation framework for ROS1 and ROS2 is awesome!



## [Brax](https://arxiv.org/abs/2106.13281)



[Github](https://github.com/google/brax)



License: Apache 2.0



Support Languages: Python



## [NVIDIA-Omniverse](https://developer.nvidia.com/nvidia-omniverse-platform)



Physics: PhysicsX



* [IsaacSim](https://developer.nvidia.com/isaac-sim)



* [IsaacGym](https://developer.nvidia.com/isaac-gym)



* [IsaacGymEnvs](https://github.com/NVIDIA-Omniverse/IsaacGymEnvs)



## [Unreal Engine](https://www.unrealengine.com/en-US/)



[Github](https://github.com/EpicGames/UnrealEngine)



To access this repository, you have to get permission from epic games



[Documentation](https://docs.unrealengine.com/4.27/en-US/)



License: Unreal Engine



Support Languages: C++



Physics Engine: PhyX



* [UnrealEnginePython](https://github.com/20tab/UnrealEnginePython) - Embed Python in Unreal Engine 4

* [UnrealCV](https://github.com/unrealcv/unrealcv) - Connecting Computer Vision to Unreal Engine

* [Carla](https://github.com/carla-simulator/carla) - Open-source simulator for autonomous driving research.



## [Unity](https://unity.com/)



* [LG SVL Simulator](https://github.com/lgsvl/simulator) - A ROS/ROS2 Multi-robot Simulator for Autonomous Vehicles



# Reinforcement Learning Toolkit



## [Open AI Gym](https://gym.openai.com/)



[Github](https://github.com/openai/gym) - A toolkit for developing and comparing reinforcement learning algorithms.



License: MIT License



Language: Python



## [ml-agents](https://github.com/Unity-Technologies/ml-agents)



License: Apache 2.0



Language: C#, Python



# Renderer



## [nvisii](https://nvisii.com/)



[Github](https://github.com/owl-project/NVISII) - A python-enabled ray tracing based renderer built on top of NVIDIA OptiX (C++/CUDA backend).



LICENSE: Apache 2.0



Launguage: C, C++



# Contributing



Your contributions are always welcome!