Open source simulator for autonomous vehicles built on Unreal Engine / Unity, from Microsoft AI & Research
Clone or download
sytelus Merge pull request #1549 from madratman/docs_vs_15.9.0_break
[readme] VS 15.9.0 is breaking airsim. use 15.8.9
Latest commit 1b5b006 Nov 16, 2018
Permalink
Failed to load latest commit information.
.vscode added demo video link for camera noise and interference Feb 13, 2018
AirLib Incorporate code review feedback on last Lidar change Nov 14, 2018
AirLibUnitTests Added DepthNav Jul 4, 2018
DroneServer Plugin refactoring to sync with AirLib (Part 2) Jun 3, 2018
DroneShell squashing last 3 commits to get rid of visuallint May 29, 2018
Examples Added data collection script Sep 7, 2018
HelloCar Plugin refactoring to sync with AirLib (Part 2) Jun 3, 2018
HelloDrone C++ API chaining, higher takeoff, Doc update - part 1 Jun 19, 2018
LogViewer Merge pull request #922 from Microsoft/review/px4_landing Apr 5, 2018
MavLinkCom merge from github/master Oct 17, 2018
PythonClient Merge pull request #1542 from alexmcroberts/patch-1 Nov 15, 2018
SGM merge from github/master Oct 17, 2018
Unity [readme] VS <=15.9.8 Nov 16, 2018
Unreal Incorporate code review feedback on last Lidar change Nov 14, 2018
cmake merge from github/master Oct 17, 2018
docs [readme] VS <=15.9.8 Nov 16, 2018
tools Enable mkdocs Nov 9, 2018
.gitignore Combining both CarDemo and DroneDemo projects under single project Un… Nov 8, 2018
.gitmodules remove, rpclib as submodule, download from git release, cmake install… Jan 20, 2018
.travis.yml Change paths to github.ip, turn of Travis Windows build, embed build … Nov 13, 2018
AUTHORS.md Updated changelog, added standard md files Nov 8, 2018
AirSim.sln Integrated SGM into example project and added data collection pipeline Aug 28, 2018
AirSim.sln.vlconfig squashing last 3 commits to get rid of visuallint May 29, 2018
CHANGELOG.md Minor doc changes Nov 14, 2018
CONTRIBUTING.md Enable mkdocs Nov 9, 2018
ISSUE_TEMPLATE.md Updated changelog, added standard md files Nov 8, 2018
LICENSE readme and license update Feb 15, 2017
README.md [readme] minor update Nov 14, 2018
SUPPORT.md Updated changelog, added standard md files Nov 8, 2018
UnrealPluginFiles.vcxproj Plugin refactoring to sync with AirLib (Part 2) Jun 3, 2018
UnrealPluginFiles.vcxproj.filters Plugin refactoring to sync with AirLib (Part 2) Jun 3, 2018
build.cmd merge from github/master Oct 17, 2018
build.sh Fix Mac build.sh clang paths Jul 6, 2018
build_docs.bat add images folder in docs build Nov 9, 2018
check_cmake.bat remove, rpclib as submodule, download from git release, cmake install… Jan 20, 2018
clean.cmd remove rd external from clean.cmd Apr 30, 2018
clean.sh fixed pushd issue in setup.sh, cmake issue with -L Jul 21, 2017
clean_rebuild.bat remove rd external from clean.cmd Apr 30, 2018
clean_rebuild.sh Better Linux upgrade steps Apr 28, 2018
install_run_all.sh Better Linux upgrade steps Apr 28, 2018
install_unreal.sh Better Linux upgrade steps Apr 28, 2018
setup.sh merge from github/master Oct 17, 2018

README.md

Welcome to AirSim

AirSim is a simulator for drones, cars and more, built on Unreal Engine (we now also have an experimental Unity release). It is open-source, cross platform, and supports hardware-in-loop with popular flight controllers such as PX4 for physically and visually realistic simulations. It is developed as an Unreal plugin that can simply be dropped into any Unreal environment. Similarly, we have an experimental release for a Unity plugin.

Our goal is to develop AirSim as a platform for AI research to experiment with deep learning, computer vision and reinforcement learning algorithms for autonomous vehicles. For this purpose, AirSim also exposes APIs to retrieve data and control vehicles in a platform independent way.

Check out the quick 1.5 minute demo

Drones in AirSim

AirSim Drone Demo Video

Cars in AirSim

AirSim Car Demo Video

What's New

For complete list of changes, view our Changelog

How to Get It

Windows

Linux

Build Status

How to Use It

Documentation

View our detailed documentation on all aspects of AirSim.

Manual drive

If you have remote control (RC) as shown below, you can manually control the drone in the simulator. For cars, you can use arrow keys to drive manually.

More details

record screenshot

record screenshot

Programmatic control

AirSim exposes APIs so you can interact with the vehicle in the simulation programmatically. You can use these APIs to retrieve images, get state, control the vehicle and so on. The APIs are exposed through the RPC, and are accessible via a variety of languages, including C++, Python, C# and Java.

These APIs are also available as part of a separate, independent cross-platform library, so you can deploy them on a companion computer on your vehicle. This way you can write and test your code in the simulator, and later execute it on the real vehicles. Transfer learning and related research is one of our focus areas.

Note that you can use SimMode setting to specify the default vehicle or the new ComputerVision mode so you don't get prompted each time you start AirSim.

More details

Gathering training data

There are two ways you can generate training data from AirSim for deep learning. The easiest way is to simply press the record button in the lower right corner. This will start writing pose and images for each frame. The data logging code is pretty simple and you can modify it to your heart's content.

record screenshot

A better way to generate training data exactly the way you want is by accessing the APIs. This allows you to be in full control of how, what, where and when you want to log data.

Computer Vision mode

Yet another way to use AirSim is the so-called "Computer Vision" mode. In this mode, you don't have vehicles or physics. You can use the keyboard to move around the scene, or use APIs to position available cameras in any arbitrary pose, and collect images such as depth, disparity, surface normals or object segmentation.

More details

Tutorials

Participate

Paper

More technical details are available in AirSim paper (FSR 2017 Conference). Please cite this as:

@inproceedings{airsim2017fsr,
  author = {Shital Shah and Debadeepta Dey and Chris Lovett and Ashish Kapoor},
  title = {AirSim: High-Fidelity Visual and Physical Simulation for Autonomous Vehicles},
  year = {2017},
  booktitle = {Field and Service Robotics},
  eprint = {arXiv:1705.05065},
  url = {https://arxiv.org/abs/1705.05065}
}

Contribute

Please take a look at open issues if you are looking for areas to contribute to.

Who is Using AirSim?

We are maintaining a list of a few projects, people and groups that we are aware of. If you would like to be featured in this list please make a request here.

Contact

Join the AirSim group on Facebook to stay up to date or ask any questions.

FAQ

If you run into problems, check the FAQ and feel free to post issues in the AirSim repository.

License

This project is released under the MIT License. Please review the License file for more details.