This repository integrates AirSim with openAI gym and keras-rl for autonomous vehicles through reinforcement learning. AirSim allows you to easly create your own environment in Unreal Editor and keras-rl let gives your the RL tools to solve the task.
My test environment binaries for Win10 can be downlaoded here.
Click here for a old (the performance is much better now) demo video:
How to use:
You can either train yourself or load the exciting weights by setting Train to True or False. CAREFUL: When you cancel the training with STRG + C, weights are saved and will overright the already trained weights.
We are taking as state input a depth image extended by the encoded information of the relative goal direction. Take a look at it by uncommenting here.
For this environment, we force the quadcopter to move in a fix plane and therefore confront the obstacles. The action space consist of three discrete actions and are available at any state:
- straight: Move in direction of current heading with 4m/s for 1s
- right yaw: Rotate right with 30°/s for 1s
- left yaw: Rotate left with 30°/s for 1s