Mobile robots with differential chassis are very often used because of simple construction and a smaller number of drive and sensors elements. For practical applications, it is necessary to know the kinematic and dynamic structure of the differential mobile robot. This paper deals with identification of the dynamics of the differential robotic platform, using differential kinematics. Electro-optical rpm sensors obtain required values such as speed of the driven wheels. Identification of dynamic system is used to determine the dynamic characteristics of power subsystem of developed EN 20 robot, whose control subsystem is created by single-chip microcontroller. Response of the dynamic system is monitored along with the peripheral velocity of the right and left drive wheels. Incremental encoders that work on optics principle measure the speeds of both wheels. It was necessary to calibrate the sensors and obtain constants for precise speed determination. The monitored system with the dumped oscillation characteristic is approximated by a system with the inertia of the 2 nd order. Dynamic system parameters are found. The system approximation is suitable for given evolution of circumferential speeds of the right and left wheels. This is confirmed by the quantitative determination coefficients R 2. The equations for calculating peripheral velocities of driving wheels are applied to the system of the differential equations for the differential chassis. A mathematical model of the mobile robot EN20 was obtained for testing control algorithms, where a robot is equipped with sensory systems and it is designed for interior conditions. Fuzzy controller with 49 interference rules is used to control the mobile robot. The real mobile robot path matches the path determined according to simulation model.

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.

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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.

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