## 1 Introduction  
Surface roughness measurements are a very important area of metrology of geometrical quantities. In general, surface roughness measurements can be divided into contactless and tactile [1; 2; 3]. Currently, a very dynamic development of contactless methods can be observed. The main reason is that contactless methods are faster than tactile methods. Furthermore, they allow the surface roughness measurement of materials susceptible to mechanical damage [4; 5]. Nevertheless, contactless methods are also not without drawbacks. For example, after measurement, there are usually a large number of unmeasured points on the tested surface. They are also sensitive to external factors, such as possible contaminants in the environment in which measurement is carried out. For this reason, tactile instruments, despite their limitations, are still widely used in industry [6; 7; 8]. When measuring roughness using the tactile method, the measuring tip moves on the surface to be measured. Due to irregularities on the surface, the measuring tip vibrates. These vibrations are amplified and converted into a signal on the basis of which surface quality is assessed. This solution was inspired by observing the behavior of the turntable needle on the surface of a gramophone record during sound playback. The principle of using needle vibrations to assess surface roughness was probably first put into practice in 1919 by [PERSON] of the National Physics Laboratory (UK) [9]. Tactile profilometers can be divided according to the type of transducer used. The most common technical solutions are profilometers with inductive, piezoelectric, and laser interference transducers. The most accurate profilometers are those equipped with a laser interference transducer. Several researchers are engaged in methods for assessing and predicting surface roughness from various points of view. These works concern, for example, predicting surface roughness based on the analysis of the machining parameters [10] or the impact of the parameters of various types of manufacturing technologies on the surface quality of the product [11; 12]. As mentioned previously, intensive research on the measurement of roughness by non-contact methods is currently underway. [PERSON] et al. in their paper [13] propose the use of image segmentation to measure the surface roughness of helical gears. Other optical methods used to measure surface roughness described in the scientific literature are the analysis of the colors of surface images [14] or multi-parameter modeling learning [15]. In the measurement of surface roughness using optical methods, techniques based on the phenomenon of light scattering on the measured surface are also used [16]. Another interesting method of analyzing the surface irregularities of products is the application of signal decomposition using a wavelet transform for this purpose [17; 18; 19; 20]. Due to the development of optical methods, the question arises regarding their accuracy in relation to the traditional tactile method. Therefore, some researchers have conducted studies comparing the results of measuring the same surface using the tactile method and selected optical methods [21; 22]. In the scientific literature, one can also find papers on the adaptation of AFM to nanoscale surface roughness in nanoscale [23]. Since surface irregularities are divided into classes: i.e., form deviations, waviness, and roughness, many research centers are working on the development of new methods for the filtration of measurement data [24; 25]. Researchers are also investigating the influence of selected factors and parameters on the result of surface roughness measurement. For example, the paper [26] describes the results of research on the influence of measurement noise, sampling interval, and digital filtering methods. One of the main parameters of surface roughness measurement using the tactile method is the tracing speed of the measuring tip. It is generally accepted that this speed should be as low as possible.