A fixed-wing UAV environment based on gymnasium.
Project description
fly-craft
An efficient goal-conditioned reinforcement learning environment for fixed-wing UAV attitude control.
Installation
Using PyPI
pip install flycraft
From source
git clone https://github.com/GongXudong/fly-craft.git
pip install -e fly-craft
Usage
import gymnasium as gym
import flycraft
env = gym.make('FlyCraft-v0')
observation, info = env.reset()
for _ in range(500):
action = env.action_space.sample() # random action
observation, reward, terminated, truncated, info = env.step(action)
if terminated or truncated:
observation, info = env.reset()
env.close()
Documentation
TODO:
Citation
Cite as
@article{gong2024flycraft,
title = {fly-craft: An Efficient Goal-Conditioned Environment for Fixed-Wing UAV Attitude Control},
author = {Xudong, Gong and Hao, Wang and Dawei, Feng and Weijia, Wang},
year = 2024,
journal = {},
}
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
flycraft-0.0.7.tar.gz
(418.8 kB
view hashes)