Algorithm for a high precision contactless measurement system

Abstract

This paper presents a Monte Carlo simulation of the self-calibration method for the multi laser tracker system (MLTS) which can track a retroreflector mounted on a kinematical system (e.g. positioning stage, robot manipulator etc.). Four laser trackers build up the MLTS. In the first part of the study the required algorithms enabling the MLTS to measure the position of the retroreflector are presented. The algorithms include the localization of the retroreflector, the communication between the laser trackers and the tracking controller as well as the calculation of the Tool Centre Point (TCP) position. In the second part of this study a deeper analysis of the self-calibration algorithm is carried out. A Monte Carlo simulation shows that the quality of the parameter estimation highly depends on the optimal arrangement of the MTLS.

Impact of the measurement uncertainty on the monitoring of thermal comfort through AI predictive algorithms

“…To quantify and access the factors that affect the outcome of a measurement process through MCM, there are two methodologies that can provide this information: sensitivity analysis and a measurement uncertainty analysis [14], [15], [16], [17]. Both of them are now applied to AI models, the first one to analyze how much each uncertainty weights on the measurement of the model's outcome and the second to identify and quantify what are the main sources of uncertainties in the measurement [18].…”