A problem of estimating the movement and orientation of a mobile robot is examined in this paper. The strapdown inertial navigation systems are often engaged to solve this common obstacle. The most important and critically sensitive component of such positioning approximation system is a gyroscope. Thus, we analyze here the random error components of the gyroscope, such as bias instability and random rate walk, as well as those that cause the presence of white and exponentially correlated (Markov) noise and perform an optimization of these parameters. The MEMS gyroscopes of InvenSense MPU-6050 type for each axis of the gyroscope with a sampling frequency of 70 Hz are investigated, as a result, Allan variance graphs and the values of bias instability coefficient and angle random walk for each axis are determined. It was found that in the output signals of the gyroscopes there is no Markov noise and random rate walk, and the X and Z axes are noisier than the Y axis. In the process of inertial measurement unit (IMU) calibration, the correction coefficients are calculated, which allow partial compensating the influence of destabilizing factors and determining the perpendicularity inaccuracy for sensitivity axes, and the conversion coefficients for each axis, which transform the sensor source codes into the measure unit and bias for each axis. The output signals of the calibrated gyroscope are noisy and offset from zero to all axes, so processing accelerometer and gyroscope data by the alpha-beta filter or Kalman filter is required to reduce noise influence.

It is suggested to use a fuzzy-neural controller for access control in CDMA networks that allows avoiding congestion in networks. The fuzzy-controller for controlling user's access has been designed. Linguistic variables, terms and membership functions for input and output values have been defined. A rule base has been developed.

In the work the non-standard system of w-parameters of the microwave quadripoles is proposed. a method of floating loads for the determination of w-parameters of microwave quadripoles is developed. the elements of the theory of the method of floating loads are proposed. new equations for determining the w-parameters of microwave quadripoles are obtained. the experimental setup for the determination of w-parameters of microwave quadripoles is developed. the results of experimental studies of w-parameters of the field transistor are obtained.

A pyroelectric temperature sensor for measuring human body temperature with increased accuracy and speed for application in mobile robotic systems has been developed. This pyroelectric temperature sensor for measuring human body temperature is intended for use in various educational institutions. Its usage will allow for identifying sick or potentially ill people and providing them with preliminary advice and avoid infecting other people. This is particularly important considering the seasonality of dangerous infectious diseases and the emergence of new ones (e.g., COVID-19). It is also advisable to use this pyroelectric sensor in hospitals, where temperature measurement is very crucial for monitoring the course of various diseases. The proposed pyroelectric temperature sensor is based on a nonlinear oscillatory system, which provides high sensitivity and allows for solving the problem of increasing the accuracy of measuring the human body temperature in a non-contact way. Measurement error is ±0.1% in the operating range (32–43) °C, measurement time—1 s, and the frequency instability is 3·10⁻⁴.

The accuracy of ultrasonic rangefinders is crucial for mobile robotic navigation systems, yet environmental factors such as temperature, humidity, atmospheric pressure, and wind conditions can influence ultrasonic speed in the air. The primary objective is to investigate how environmental factors influence the output signal of an ultrasonic emitter and to develop a method for improving the accuracy of distance measurements in both outdoor and indoor settings. The research employs a combination of theoretical modeling, statistical analysis, and experimental validation. The research employs an ultrasonic rangefinder integrated with environmental sensors (BME280, Bosch Sensortec GmbH, Kusterdingen, Germany) and wind sensors (WMT700, WINDCAP^®, Vaisala Oyj, Vantaa, Finland) to account for environmental influences. Experimental studies were conducted using a prototype ultrasonic rangefinder, and statistical analysis (Student’s t-test) was performed on collected data. The results of estimation by Student’s t-test for 256 measurements demonstrate the maximum effect of air temperature and the minimum effect of relative air humidity on a piezoelectric emitter output signal both outdoors and indoors. In addition, wind parameters affect the rangefinder’s operation. The maximum range of obstacle detection depends on the reflection coefficient of the material that covers the obstacle. The results align with theoretical expectations for highly reflective surfaces. A cascade-forward artificial neural network model was developed to refine distance estimations. This study demonstrates the importance of considering environmental factors in ultrasonic rangefinder systems for mobile robots. By integrating environmental sensors and using statistical analysis, the accuracy of distance measurements can be significantly improved. The results contribute to the development of more reliable navigation systems for mobile robots operating in diverse environments.