A novel approach to control the Jointed Arm Robot by tracking the position of the moving object on a conveyor using Integrated Computer Vision system


Computer vision algorithms play a vital role in developing self-sustained autonomous systems. This paper aims to develop an approach to control the jointed arm robot based on the position of the moving object using integrated computer vision. In this work, a simple web camera placed above the work cell to capture the continuous images of a conveyor and a jointed arm robot that connected to a microcontroller through the computer. The position of an object tracked, and its features are extracted from the captured image frame by subtracting its background using the Gaussian Mixture Model (GMM). The output images of GMM further processed by image processing techniques to extract the shape, color, center coordinates. The extracted coordinates of the objects of interest used as input for the controller to activate the base rotation of a joint arm robot to perform different manipulations. The algorithm evaluated on an indigenously fabricated work cell integrated with a computer vision setup.

Mechanical Engineering (1)