gym_multirotor
Gym to train reinforcement learning agents on UAV platforms
Quadrotor | Tiltrotor |
---|---|
Requirements
This package has been tested on Ubuntu 18.04 with python 3.6
.
python=3.6
numpy
scipy
gym
mujoco_py
Installation
To install, you will have to clone this repository on your personal machine. Follow the below commands:
$ git clone https://github.com/adipandas/gym_multirotor.git
$ cd gym_multirotor
$ pip install -e .
Environments
List of environments available in this repository include:
Environment-ID | Description |
---|---|
QuadrotorPlusHoverEnv-v0 |
Quadrotor with + configuration with task to hover. |
TiltrotorPlus8DofHoverEnv-v0 |
Tiltrotor with + configuration. |
QuadrotorXHoverEnv-v0 |
Quadrotor with x configuration with a task to hover. |
References
Citation
If you find this work useful, please cite our work:
@inproceedings{deshpande2020developmental,
title={Developmental reinforcement learning of control policy of a quadcopter UAV with thrust vectoring rotors},
author={Deshpande, Aditya M and Kumar, Rumit and Minai, Ali A and Kumar, Manish},
booktitle={Dynamic Systems and Control Conference},
volume={84287},
pages={V002T36A011},
year={2020},
organization={American Society of Mechanical Engineers}
}
Notes:
- Some of the environment parameters have been updated but the task of these drone environments still remains the same as what was discussed in the paper.
- I will keep on updating these codes as I make further progress in my work.