Robot control method based on distance measurement

This article is dedicated to the exploration of methods for calibrating the kinematic parameters of robots aimed at minimizing errors arising from deviations in the geometry of structures and assembly. Key calibration approaches are discussed, including direct and inverse calibration, data filtering methods, optimization using the least squares method, and the use of modern measuring devices such as laser trackers and coordinate measuring machines (CMM). The role of machine learning in enhancing the accuracy and flexibility of the calibration system is also analyzed. The application of these methods allows for improved positioning accuracy of robots, which is crucial for their effective operation in various industrial fields.