Using Camera

To use the camera, you need to install openCV. We require the contrib version, which provides support for ArUco tags. To include opencv-contrib-python in the installation, you can use the following command:

pip install nuro-arm[all]

Capturing Images

from nuro_arm import Camera

cam = Camera()

img = cam.get_image()


If you want to associate features in the image with positions in the real world, then the camera must be calibrated.

Using ArUco Tags

ArUco Tags are visual markers that look like QR codes. Due to their unique appearance, they can be easily located in an image using a computer vision algorithm. By placing them on an object, we can determine the object’s 3D position, which can be used for a robotics task.

To generate a PDF of ArUco Tags, use the generate_aruco_tags script. Here is an example that creates four aruco tags (ids 0 to 3) with a size of 40 millimeters.

generate_aruco_tags --size=40 --number=4

To locate ArUco Tags in an image:

from import find_arucotags

tag_size = 0.040 # size in meters
tags = find_arucotags(img, tag_size)