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RL_rocket

Trajectory

Repository for the development of my master thesis on control of launch vehicles descent and landing through reinforcement learning actors.

Separate Gym environment available.

6DOF problem

In this repository a full 6DOF rocket landing environment is developed, with realistic dynamics equation modeled on a rigid body assumption.

Continuous action space

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 $\delta_y$ and $\delta_z$ around two hinge points, respectively moving the engine around the z and y axis.

Docker

To run the algorithm in a Docker container follow these steps:

  1. Clone the repository

  2. Build the docker image docker build -t rl_rocket_docker .

  3. Get your Wandb API key from wandb.ai/authorize

  4. 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