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https://github.com/tawnkramer/gym-donkeycar
OpenAI gym environment for donkeycar simulator
https://github.com/tawnkramer/gym-donkeycar
Last synced: 14 days ago
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OpenAI gym environment for donkeycar simulator
- Host: GitHub
- URL: https://github.com/tawnkramer/gym-donkeycar
- Owner: tawnkramer
- License: other
- Created: 2018-10-13T19:48:14.000Z (about 6 years ago)
- Default Branch: master
- Last Pushed: 2024-03-17T06:56:26.000Z (8 months ago)
- Last Synced: 2024-10-23T01:18:57.516Z (22 days ago)
- Language: Python
- Homepage:
- Size: 3.04 MB
- Stars: 193
- Watchers: 13
- Forks: 115
- Open Issues: 1
-
Metadata Files:
- Readme: README.md
- Changelog: HISTORY.rst
- Contributing: CONTRIBUTING.rst
- License: LICENSE
- Authors: AUTHORS.rst
Awesome Lists containing this project
README
# OpenAI Gym Environments for Donkey Car
[](https://pypi.python.org/pypi/gym-donkeycar) [](https://github.com/tawnkramer/gym-donkeycar/actions) [](https://gym-donkeycar.readthedocs.io/en/latest/?badge=latest)
Donkey Car OpenAI Gym
- Free software: MIT license
- Documentation:
## Installation
Download simulator binaries: https://github.com/tawnkramer/gym-donkeycar/releases
Install master version of gym donkey car:
```shell
pip install git+https://github.com/tawnkramer/gym-donkeycar
```
## Example Usage
A short and compact introduction for people who know gym environments,
but want to understand this one. Simple example code:
```python
import os
import gym
import gym_donkeycar
import numpy as np
# SET UP ENVIRONMENT
# You can also launch the simulator separately
# in that case, you don't need to pass a `conf` object
exe_path = f"{PATH_TO_APP}/donkey_sim.exe"
port = 9091
conf = { "exe_path" : exe_path, "port" : port }
env = gym.make("donkey-generated-track-v0", conf=conf)
# PLAY
obs = env.reset()
for t in range(100):
action = np.array([0.0, 0.5]) # drive straight with small speed
# execute the action
obs, reward, done, info = env.step(action)
# Exit the scene
env.close()
```
or if you already launched the simulator:
```python
import gym
import numpy as np
import gym_donkeycar
env = gym.make("donkey-warren-track-v0")
obs = env.reset()
try:
for _ in range(100):
# drive straight with small speed
action = np.array([0.0, 0.5])
# execute the action
obs, reward, done, info = env.step(action)
except KeyboardInterrupt:
# You can kill the program using ctrl+c
pass
# Exit the scene
env.close()
```
- see more examples: https://github.com/tawnkramer/gym-donkeycar/tree/master/examples
## Action space
A permissable action is a numpy array of length two with first steering
and throttle, respectively. E.g. `np.array([0,1])` goes straight at full
speed, `np.array([-5,1])` turns left etc.
Action Space: Box(2,)
Action names: `['steer', 'throttle']`
What you receive back on step:
- obs: The image that the donkey is seeing (np.array shape
(120,160,3))
- reward: a reward that combines game over, how far from center and
speed (max=1, min approx -2)
- done: Boolean. Game over if cte > max_cte or hit != "none"
- info contains:
- cte: Cross track error (how far from center line)
- positions: x,y,z
- speed: positive forward, negative backward
- hit: 'none' if all is good.
- last_lap_time: time of last successful lap in seconds, 0.0 if there isn't one
Example info:
```python
{'pos': (51.49209, 0.7399381, 117.3004),
'cte': -5.865292,
'speed': 9.319956,
'hit': 'none',
'last_lap_time': 34.93437361717224}
```
## Environments
- "donkey-warehouse-v0"
- "donkey-generated-roads-v0"
- "donkey-avc-sparkfun-v0"
- "donkey-generated-track-v0"
- "donkey-roboracingleague-track-v0"
- "donkey-waveshare-v0"
- "donkey-minimonaco-track-v0"
- "donkey-warren-track-v0"
- "donkey-thunderhill-track-v0"
- "donkey-circuit-launch-track-v0"
## Codestyle
We are using [black codestyle](https://github.com/psf/black) (max line length of 127 characters) together with [isort](https://github.com/timothycrosley/isort) to sort the imports.
**Please run `make format`** to reformat your code. You can check the codestyle using `make check-codestyle` and `make lint`.
## Tests
Type checking with `pytype`:
```
make type
```
Codestyle check with `black`, `isort` and `ruff`:
```
make check-codestyle
make lint
```
To run `pytype`, `format` and `lint` in one command:
```
make commit-checks
```
Build the documentation:
```
make docs
```
## Credits
Original Source Code
Tawn Kramer -
Roma Sokolkov - cloned with
permission from
Maintainer
Maxime Ellerbach -
Release Engineer
Leigh Johnson: https://github.com/leigh-johnson
This package was created with
[Cookiecutter](https://github.com/audreyr/cookiecutter) and the
[audreyr/cookiecutter-pypackage](https://github.com/audreyr/cookiecutter-pypackage)
project template.