Hand–Eye Calibration Using a Tablet Computer

• Published in: Mathematical and computational applications Vol. 28; no. 1; p. 22
• Main Author: Sato, Junya
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01.02.2023
• Subjects: Analysis; Automobile equipment and supplies industry; Calibration; Cameras; Computer-aided design; differential evolution; End effectors; evolutionary computation; hand–eye calibration; Mathematical analysis; Mathematical models; Neural networks; Portable computers; Robots; tablet computer; Tablet computers; Japan
• ISSN: 2297-8747; 1300-686X; 2297-8747
• DOI: 10.3390/mca28010022

Many approaches have been developed to solve the hand–eye calibration problem. The traditional approach involves a precise mathematical model, which has advantages and disadvantages. For example, mathematical representations can provide numerical and quantitative results to users and researchers. Thus, it is possible to explain and understand the calibration results. However, information about the end-effector, such as the position attached to the robot and its dimensions, is not considered in the calibration process. If there is no CAD model, additional calibration is required for accurate manipulation, especially for a handmade end-effector. A neural network-based method is used as the solution to this problem. By training a neural network model using data created via the attached end-effector, additional calibration can be avoided. Moreover, it is not necessary to develop a precise and complex mathematical model. However, it is difficult to provide quantitative information because a neural network is a black box. Hence, a method with both advantages is proposed in this study. A mathematical model was developed and optimized using the data created by the attached end-effector. To acquire accurate data and evaluate the calibration results, a tablet computer was utilized. The established method achieved a mean positioning error of 1.0 mm.