aicoe-donkeycar

donkeycar: a python self driving library

Donkeycar is minimalist and modular self driving library for Python. It is developed for hobbyists and students with a focus on allowing fast experimentation and easy community contributions.

NOTE: this package is a non-official build by the AICoE. Please check the upstream project links for official information.

Quick Links

• Donkeycar Updates & Examples
• Build instructions and Software documentation
• Discord / Chat

Use Donkey if you want to:

• Make an RC car drive its self.
• Compete in self driving races like DIY Robocars
• Experiment with autopilots, mapping computer vision and neural networks.
• Log sensor data. (images, user inputs, sensor readings)
• Drive your car via a web or game controller.
• Leverage community contributed driving data.
• Use existing CAD models for design upgrades.

Get driving.

After building a Donkey2 you can turn on your car and go to http://localhost:8887 to drive.

Modify your cars behavior.

The donkey car is controlled by running a sequence of events

#Define a vehicle to take and record pictures 10 times per second.

import time
from donkeycar import Vehicle
from donkeycar.parts.cv import CvCam
from donkeycar.parts.tub_v2 import TubWriter
V = Vehicle()

IMAGE_W = 160
IMAGE_H = 120
IMAGE_DEPTH = 3

#Add a camera part
cam = CvCam(image_w=IMAGE_W, image_h=IMAGE_H, image_d=IMAGE_DEPTH)
V.add(cam, outputs=['image'], threaded=True)

#warmup camera
while cam.run() is None:
    time.sleep(1)

#add tub part to record images
tub = TubWriter(path='./dat', inputs=['image'], types=['image_array'])
V.add(tub, inputs=['image'], outputs=['num_records'])

#start the drive loop at 10 Hz
V.start(rate_hz=10)

See home page, docs or join the Discord server to learn more.