The paper considers active stabilization of a laser gyro path length in a wide range of temperatures, using a movable mirror with a piezoceramic drive. Analysis of the main designs of piezo adjusters used in the laser gyros made in Russia is presented. Computer models of piezo adjusters have been developed to study the distortions and curvatures of piezo-driven mirror surfaces based on their resonant oscillatory characteristics. By comparing the calculated data and the experimental results, a relationship between the movements of mirrors and the output parameters of laser gyroscopes has been found. Possible improvements of piezo adjuster structures are proposed, which make it possible to increase the accuracy and performance characteristics of laser gyroscopes.

Concern CSRI Elektropribor, JSC, has accumulated extensive experience in the development and application of electrostatic suspensions (ESS) of sensitive masses of various inertial sensors – gyroscopes and accelerometers. The article presents the schemes that form the basis of these devices. An attempt is made to generalize the principles of construction and search for unified approaches to the creation of inertial sensors using ESS.

Micro rotating disk gyroscopes (μRDGs) have emerged as a contender for replacing vibratory gyroscopes as crucial components in consumer electronics due to their high accuracy, precision, stability and wide dynamic range in motion sensing, image stabilisation, etc. However, effective thermal management remains a challenge in maximising their performance and reliability, especially at high heat loads, thus helping downsize μRDGs and enabling them as a potential component in consumer electronics. This study investigates the potential of using nanofluids for thermal performance enhancement of μRDGs. The research examines Zirconium dioxide nanoparticles dispersed in water as the base fluid. Five concentrations of ZrO₂ nanoparticles – 0.2%, 0.4%, 0.6%, 0.8% and 1% – have been investigated. Moreover, the study incorporates five varying rotational speeds across all five concentrations. Additionally, surface roughness values of 0.025, 0.05 and 0.1, represented in dimensionless form, are examined in conjunction with the ensuing speeds and concentrations of nanoparticles. The utilisation of nanoparticles is observed to enhance the heat dissipation capability. Notably, at an angular velocity of 1000 rad/s and a nanoparticle concentration of 1%, the maximum enhancement in heat dissipation reaches approximately 27%. Surface roughness demonstrates minimal impact regardless of its values, with a maximum heat dissipation increase of 0.31%. Additionally, graphical representations of various performance indices are provided. The findings of this research indicate promising prospects for improving the thermal performance of μRDGs by utilising nanofluids in conjunction with angular speeds at high heat loads of 500 W/cm², thus helping in the miniaturisation of these components for viable use in consumer electronics.

The paper considers the problem of traffic lights identification (detection, filtering and map-matching) using successive images in active aid systems for tram drivers, equipped with multiple cameras with different focal lengths. The process of the problem solution is described in detail, from measurements (detections) formed at the neural network output for each of the cameras, and up to the results matching with a map. In contrast to other studies of this subject, the authors of this work use 3D measurements as the output data for the neural network, and unscented Kalman filter (UKF) for determining the position of the traffic lights; in addition, a new method for fusing the data from two cameras is applied. The efficiency of the proposed algorithms and its modification has been field-tested. The results of experiments have shown that the algorithm provides the accuracy of 76.19% and completeness of 97.46% when used in combination with the tram control system with two cameras.

Astronomical calibration is defined as determination of the constant attitude of digital cameras relative to the inertial measurement unit using ground-based star observations. The first part of this paper [1] focuses on the calibration of relative attitude of all cameras, which provides combination of their separate measurements into the observations of one virtual camera. The second part examines the calibration of virtual camera attitude relative to the inertial measurement unit (IMU). The calibration is performed on a simple test bench, which is unable to set the accurate attitude of the calibrated unit relative to the stars. Therefore, the calibrated parameters are estimated by the attitude increments over a time period between the astronomical measurements. Formulas for calculating the attitude increments from the inertial and astronomical measurements and their covariance matrices have been obtained. It has been shown that not all calibration trajectories provide unambiguous estimation of the calibrated parameters based on the attitude increments. The necessary condition for selecting the required trajectories has been formulated. The formula for finding the error covariance matrix of IMU attitude by the astronomical measurements has been received. This formula considers the star configuration observed with the virtual camera, its calibration errors described in the first part of the paper, and calibration errors in its attitude relative to the IMU obtained in the second part. The RMS error of the attitude calibration is experimentally found to be about 6 arcsec.

The paper proposes an algorithm for detecting the railway defects by the readings of inertial sensors, taking into account the bolted joints passed. The mathematical tools used in this method include continuous wavelet transform and frequency domain analysis. The algorithm has been tested with an experimental data sample, and the efficiency of its application has been demonstrated.

This study proposes an autonomous navigation approach for the Pioneer P3-DX Autonomous Wheeled Robot (AWR) in environments containing both static and dynamic obstacles. The robot utilizes the Artificial Potential Field (APF) algorithm for path calculation, while a neural network aids in zone classification. Three ultrasonic sensors provide distance measurements for hazard assessment. These measurements, along with relative velocity and angle data, aid in identifying regions of elevated risk (Zone 1) and those of lesser risk (Zone 2). Upon hazard detection, fuzzy logic facilitates effective collision avoidance by adjusting wheel velocities. Simulation results conducted in MATLAB and V-REP demonstrate the approach’s efficacy in navigating diverse obstacles, showcasing its adaptability and resilience compared to alternative algorithms. This research introduces an innovative methodology for autonomous mobile robot navigation, emphasizing its reliability and efficiency in traversing intricate environments with varying risk levels.