Optimizing the position of a robotic arm using statistical methods

Abstract

Robotics plays a key role in industry, and its use continues to grow. Robots are used in many sectors to increase the efficiency, productivity, and safety of work processes. This manuscript focuses on the spatial calibration of collaborative robot arms using appropriate statistical tools. Nowadays, there are many dedicated programming languages, simulations or virtual reality (VR), which in most cases perform calibration using matrix relations. The mathematical-statistical solution is not often addressed, and the use of linear relationships is valid only in certain parts of the workspace of the collaborative robot. The purpose of this article is to demonstrate how to find a suitable statistical method that would respect the wear of the arm mechanism in predefined positions based on the requirements of ISO 230–2:2015. Based on these measurements, it is possible to assume that optimal solutions can be obtained using a polynomial regression function. This optimization method will be explored using the Newton and Markwartel methods.