nav-gym

A OpenAI-gym compatible navigation simulator, which can be integrated into the robot operating system (ROS) with the goal for easy comparison of various approaches including state-of-the-art learning-based approaches and conventional ones.

Note: This reporsitory is part of ICRA 2023 paper. Please visit our hrl-nav repo for more details.

Install

The package has been tested on Ubuntu 18.04 / Python 3.6 / ROS Melodic.

To install without ROS-supported:

virtualenv ~/venv/hrlnav --python=python3.6
source ~/venv/hrlnav/bin/activate

git clone https://github.com/leekwoon/nav-gym.git

cd nav-gym/nav_gym
pip install -e .

To install with ROS-supported:

virtualenv ~/venv/hrlnav --python=python3.6
source ~/venv/hrlnav/bin/activate

cd ~/YOUR_CATKIN_WORKSPACE/src
git clone https://github.com/leekwoon/nav-gym.git

# install nav_gym_env
cd nav-gym/nav_gym
pip install -e .

cd ~/YOUR_CATKIN_WORKSPACE
catkin_make -DPYTHON_EXECUTABLE=/usr/bin/python3
source devel/setup.bash # or you can write it on ~/.bashrc

Usage

import gym
import nav_gym_env

env = gym.make("NavGym-v0")
obs = env.reset()

done = False
while not done:
    action = env.action_space.sample() # Your agent code here
    obs, reward, done, info = env.step(action)
    env.render()

We recommend installing our package with ROS-supported since RViz visualization is fast and interactive. If you want to use RViz visualization, first run:

roslaunch nav_gym start_nav_gym.launch

and in another terminal, run:

roslaunch nav_gym view_robot.launch

now we can simulate:

import gym
import nav_gym_env
from nav_gym_env.ros_env import RosEnv

env = gym.make("NavGym-v0")
env = RosEnv(env)
obs = env.reset()

done = False
while not done:
    action = env.action_space.sample() # Your agent code here
    obs, reward, done, info = env.step(action)

Reference

@software{lee2023nav,
  author={Lee, Kyowoon and Kim, Seongun and Choi, Jaesik},
  title={nav-gym},
  url={https://github.com/leekwoon/nav-gym},
  year={2023}
}

License

This repository is released under the MIT license. See LICENSE for additional details.

Credits

Our codebase builds based on all-in-one-DRL-planner, navrep and flatland.