Rover4We-v1

Here is the code to environment used in the simulations of the paper "Visual and Dynamics Fusion on a Deep Reinforcement Learning Controlled Rover".

We used the following python libraries: tensorflow (https://www.tensorflow.org/) and gym (https://gym.openai.com/). Simulation was performed with MuJoCo (http://www.mujoco.org/)

Instaling the Environment

If $GYM is your path to the gym folder

The files inside mujoco folder must be in: $GYM/gym/envs/mujoco

The files inside mujoco/assets folder must be in: $GYM/gym/envs/mujoco/assets

Add the following lines of code in the :$GYM/gym/envs/__init__.py file

register(
    id='Rover4We-v1',
    entry_point='gym.envs.mujoco:RoverRobotrek4Wev1Env',
    reward_threshold=1000,
    )

Add the following line of code in the :$GYM/gym/envs/mujoco/__init__.py file

from gym.envs.mujoco.rover_4We_v1 import RoverRobotrek4Wev1Env