Hydrone Gym env

This is a gym env to work with the hydrone gazebo simulations, allowing the use of OpenAI Baselines and Stable Baselines deep reinforcement learning algorithms in the robot navigation training.

This project is a part of the development of some gazebo environments to apply deep-rl algorithms.

Research Gazebo environments for hydrone robot

Installation

git clone https://github.com/ricardoGrando/hydrone_deep_rl_lars
git clone https://github.com/ricardoGrando/gym_hydrone
cd gym_hydrone
pip install -e .

This is an example using the OpenAI Baselines DDPG algorithm in a hydrone environment.

.\examples\openai_baselines_ddpg.py:

import gym
import gym_hydrone
import rospy
import os

env = gym.make('hydrone_Circuit_Simple-v0', env_stage=1, observation_mode=0, continuous=True, goal_list=None)

To cite this repository in publications:

@misc{gymhydrone,
  author = {Grando, Ricardo},
  title = {gym-hydrone},
  year = {2022},
  publisher = {GitHub},
  journal = {GitHub repository},
  howpublished = {\url{https://github.com/ricardoGrando/gym_hydrone}},
}

hydrone_gym