Real-time vision-based controller for delta robots

Abstract

This paper investigates two real-time vision-based control algorithms for delta robots. The first one aims to enable the robot to track different objects based on their colours and shapes. This algorithm does not need any initial calibration. Instead, it depends on the least squares algorithm (LSA) to generate the required transformation matrixes. Also, it is implemented on a standalone controller with no additional time complexity added to the main controller. The second one is a self-calibrating human hand gesture tracking algorithm, which can perform automatic calibration and generates transformation matrixes automatically based on the initial measurements of the user's body. The algorithms are designed, implemented, and scheduled in a real-time manner. The results show that these algorithms can track fast-moving objects effectively regardless of the initial configuration of the robot. They provide important solutions for common problems related to visual servoing such as field of view and calibration.