AirSim (Aerial Informatics and Robotics Simulation) is an open-source, cross platform simulator for drones, ground vehicles such as cars and various other objects, built on Epic Games’ proprietary Unreal Engine 4 as a platform for AI research.[2] It is developed by Microsoft and can be used to experiment with deep learning, computer vision and reinforcement learning algorithms for autonomous vehicles.[3][4] This allows testing of autonomous solutions without worrying about real-world damage.[5]
AirSim provides some 12 kilometers of roads with 20 city blocks and APIs to retrieve data and control vehicles in a platform independent way. The APIs are accessible via a variety of programming languages, including C++, C#, Python and Java. AirSim supports hardware-in-the-loop with driving wheels and flight controllers such as PX4 for physically and visually realistic simulations. The platform also supports common robotic platforms, such as Robot Operating System (ROS).[6] It is developed as an Unreal plug-in that can be dropped into any Unreal environment.[7] An experimental release for a Unity plug-in is also available.[8][9]
See also
References
- ^ "Tags · microsoft/AirSim · GitHub". GitHub AirSim repository. Retrieved 2022-07-20.
- ^ "Microsoft AI simulator includes autonomous car research". www.digitaljournal.com. November 26, 2017.
- ^ "Open source simulator for autonomous vehicles built on Unreal Engine / Unity, from Microsoft AI & Research: Microsoft/AirSim". GitHub. 30 March 2020.
- ^ "Microsoft AirSim, a Simulator for Drones and Robots". InfoQ.
- ^ Vallance, Chris (18 July 2022). "Microsoft launches simulator to train drone AI systems". BBC News. Retrieved 20 July 2022.
- ^ "Aerial Informatics and Robotics Platform". Microsoft Research.
- ^ "Aerial Autonomy: Project AirSim". Microsoft AI.
- ^ "AirSim on Unity: Experiment with autonomous vehicle simulation". blogs.unity3d.com. November 14, 2018.
- ^ "Microsoft's open source AirSim platform comes to Unity". VentureBeat. November 14, 2018.
Further reading
- Shital Shah; Debadeepta Dey; Chris Lovett; Ashish Kapoor (2017-11-03). "AirSim: High-Fidelity Visual and Physical Simulation for Autonomous Vehicles". arXiv:1705.05065 [cs.RO].
