Repository for the development of my master thesis on control of launch vehicles descent and landing through reinforcement learning actors.
In this repository a full 6DOF rocket landing environment is developed, with realistic dynamics equation modeled on a rigid body assumption.
The environment employes a continuous action space, with the engine allowed to throttle between maxThrust
and minThrust
. The thrust was normalized to lie in the range [-1, +1]
as best practice for convergence of the algorithms suggest. The engine is gimbaled by two angles
To run the algorithm in a Docker container follow these steps:
-
Clone the repository
-
Build the docker image
docker build -t rl_rocket_docker .
-
Get your Wandb API key from wandb.ai/authorize
-
Start the docker container passing the API key as an environmental variable (paste it in place of
$YOUR_API_KEY$
)docker run -e WANDB_API_KEY=$YOUR_API_KEY$ -it rl_rocket_docker