This paper deals with the determination of the absolute errors of a small time of flight (ToF) distance sensor with respect to coloured surfaces at different illumination intensities. The aim was to determine the absolute error of the measured distance by the VL53L1X sensor when set to short-mode and long-mode at different illumination intensities: 10 lx and 350 lx depending on the coloured surface using regression analysis methods. The research was performed using 7 colour samples with different spectral colours determined according to the CIE Lab colour model. Based on the performed experiments, it was found that the error at different sensor settings, change of colour surface and different illumination intensity is approximated by a linear function only up to a certain measured distance. The process is influenced by proposed factors such as: illumination intensity, coloured surface with different illumination reflectance and signal-noise parameters of the tested sensor during the experiment.

The application of intelligent control algorithms in the field of autonomous mobile robotics enables effective control of mobile robots with a minimal possible error. At present, most of commonly used systems to control an autonomous mobile robot are, however, too complicated to design. Our goal was to design a fuzzy controller with an optimal number of inference rules in a way to achieve the best possible level of quality of mobile robot control. The proposed controller was implemented in the mobile robot EN20, where the time of regulation and the absolute and the quadratic control surface were used to evaluate quality parameters. The analysis of the quality of control was performed with the use of a fuzzy controller with 9, 25 and 49 inference rules. We found from the results of modelling that the greatest influence on the quality of control of a mathematical model of the mobile robot had the number of inference rules of the fuzzy controller. Mathematical and graphical dependence of the quality of control on the number of inference rules was calculated from the parameters of the quality of control. The results of the research are equations of the curves of the individual parameters of control of quality, which show that for the control of the autonomous mobile robot EN 20, that the optimal fuzzy controller has 49 inference rules, triangular functions of the pertinence of individual linguistic values and it is defuzzificated by Centroid method.

At present, there are several types of propellers in the field of the use of Unmanned Aerial Vehicles (UAVs) with unknown parameters, where it is necessary to provide information about their thrust, current consumption and maximal rotational speed (RPM). Commonly used methods for measurement of a propeller's thrust are mostly based on the usage of a single purpose system, on short measurements without data storage or on inaccurate sensors. The goal of this article is to develop a universal experimental measuring system for more accurate measurement of propeller's parameters (thrust, current consumption, maximal RPM). For more accurate measurement, the battery voltage, temperature and humidity of the environment were also measured. To acquire, measure and store the data safely on a micro SD card, a processing circuit based on an ATmega2560 microcontroller was developed. This innovative approach allowed to analyse the behaviour of the propeller and to measure the dependencies of the RPM on pulse width, of the current on RPM and of the thrust on RPM at different input conditions. The measurements have shown that the dependencies can be approximated by cubic functions. The mathematical description allows predicting the behaviour of the propeller in unmeasurable conditions.