Calibration and Offset Mitigation of End-Effector Cameras Using ARUCO Markers

Abstract

This thesis focuses on the exploration and evaluation of various computer vision algorithms to calculate and mitigate the offset of an end-effector camera. Focusing on ARUCO markers, the project investigates and compares methods for precise camera calibration. By analyzing and determining the most effective methods, this work aims to improve the precision and reliability of camera alignment in robotic systems, enabling enhanced performance in tasks requiring accurate visual feedback.