The problem of approximately determining the reliability characteristics of a redundant cold-reserve system with unlimited recovery in a non-homogeneous case is considered. For the constructed semi-Markov model with a phase space of states of a general form, under the condition of “rapid” recovery of the system’s elements, the algorithm of asymptotic phase merging is applied, which makes it possible to obtain formulas for the approximate determination of steady-state reliability characteristics in a non-homogeneous case and to analyze their errors. In addition, an expression is obtained for the approximate calculation of the probability of failure-free operation of the system under consideration. The research results can be used to analyze the reliability of redundant radio engineering, information, energy, and some other systems at their design and operation stages.

The methods for managing the group behavior of autonomous service units are presented, and the results of their advantages and disadvantages are analyzed. A formalized formulation and quality indicators for solving the problem of optimal planning of a heterogeneous group of service units are provided. Based on the results of numerical studies, a combined planning methodology is proposed, which takes into account the specifics of the particular problem formulation, the requirements for solution quality, and the advantages of specific methods for solving the combinatorial optimization problems.

A methodology for synthesizing the structure of an unmanned system using an algorithm of multi-agent swarm optimization is proposed. Based on the concept of multi-agent technologies, the possibility of developing a unified approach to solving the problem of effectively constructing the structure of a group of unmanned aerial vehicles in a dynamically changing environment is substantiated. The structure of a meta-heuristic algorithm describing the functioning process of an unmanned system with the possibility of dynamic reconfiguration is considered. A methodology for synthesizing a stable structure of an unmanned system for the rational distribution of its elements in space, taking into account the criteria of effectiveness, speed, and resource intensity, is proposed. The methodology is implemented based on a two-stage approach to the virtual calculation of positions using a swarm optimization algorithm for subsequent physical movement. A software implementation of the methodology has been developed. Results of numerical studies of the effectiveness of the synthesized structure are presented using computational examples.

Reliable 6D object pose estimation is a foundational capability for robotic manipulation in Industry 4.0 and unstructured warehouse environments. Current state-of-the-art methods, such as PVN3D and SAM-6D, predominantly rely on “Model-Based” paradigms that necessitate high-fidelity CAD models of the target objects for training or template matching. This requirement severely limits their applicability in open-world scenarios where such CAD models are unavailable in real-time. To bridge this gap, a novel 6D Pose Estimation Framework without fine-tuning on the target object (Zero-Shot) is proposed to eliminate the dependency on prior CAD models. A single-view 3D generative model is leveraged to synthesize a geometrically plausible 3D mesh from a single RGB image. To address the scale ambiguity inherent in generative models, which poses a critical challenge for robotic grasping, a Template-Prior Iterative Closest Point (TP-ICP) based on the classical ICP is introduced for iterative recovery of the metric scale. This algorithm robustly recovers the metric physical scale of the neural-generated mesh using depth information, employing median-based outlier removal and template-guided ICP to handle occlusions and sensor noise. The recovered metric mesh is then seamlessly integrated into a standard 6D pose estimation pipeline, establishing a closed-loop framework comprising model self-generation, metric scale calibration, and pose estimation. A fully reproducible implementation scheme is presented. Systematic experiments on the LINEMOD dataset demonstrate that the proposed approach achieves robust 6D pose estimation suitable for robotic tasks, even in the complete absence of prior CAD models.

The main goal of the work is to demonstrate the features of the technical and software implementation of the method for determining the water flow velocity in rivers and channels by recording and processing video images of the water surface, as well as to analyze the effectiveness of the method in comparison with standard measurements using a hydrometric turbine and the float method. A brief overview of the most commonly used methods for determining flow velocity is provided. The stages of software processing of the obtained video data and the methodology for determining the average flow velocity based on cross correlation analysis of images are considered. The results of the method’s testing are presented, confirming its effectiveness; the discrepancies with the results obtained using a certified hydrometric vane generally do not exceed 11 %. This method allows for the rapid acquisition of data on flow velocity in rivers and canals without the use of expensive equipment. A distinctive feature of the method is the ability to determine the flow velocity field across the entire cross section of the water body under study, which makes it possible to obtain more accurate data compared to standard measuring tools.

Results of assessing the total standard uncertainty of experimental measurements of the thermal conductivity coefficient of thermal insulation materials with significant internal heterogeneity are presented. The measurements are carried out using the reference standard method and a virtual test bench. The distinctive feature of this measurement method is the application of a constant thermal load to two reference objects with high thermal conductivity: one of them is shielded from the surrounding environment by a sample of the material under study, while the other is in the surrounding environment. Based on the difference in heating rates of two reference objects, the thermal conductivity coefficient of the material under study is determined using the calibration characteristic of the experimental setup, which is obtained by means of a virtual copy of the setup in a CAE program. To improve the accuracy of the method, a dimensionless difference in the heating rates of the two reference objects is used, which required the application of the results of experimental and virtual studies of a third reference sample with a known thermal conductivity coefficient. A methodology for assessing the total standard uncertainty of measuring the thermal conductivity coefficient of a thermal insulation material using the method of etalons is developed, and the optimal method for processing the results of experimental and virtual studies is selected. According to the calculations, the total standard uncertainty in measuring the thermal conductivity coefficient using the reference standard method is ±0.0136 W/(m·K).

The task of developing and implementing an automated analyzer, which is a multi-module measuring system for determining the mass fraction of organochlorine compounds in crude oil, is considered. A distinctive feature of the task is ensuring high measurement sensitivity. The proposed approach is based on implementing a microcoulometric method for determining the mass fraction of organochlorine compounds after high-temperature combustion of the prepared sample in a stream of oxygen and an inert gas. The quantitative assessment of the chlorine content is carried out based on the equiatomic reaction between chlorine and silver ions, which must be pre-generated in the electrolyte. According to Faraday’s law, the amount of present chlorine is calculated by integrating the silver ion generation current in a coulometric cell. The technological parameters are controlled using proportional-integral control implemented on a programmable logic controller. The software implementation of the analyzer’s operating algorithm provides for the automated execution of all measurement stages, the registration of sensor signals, and the calculation of the mass fraction of chlorine, taking into account the volume and density of the introduced sample. The developed and implemented automated analyzer ensures that measurements are carried out in accordance with regulatory requirements and has a high degree of automation. The architecture of the hardware-software complex is developed, and algorithms for processing the measuring signal is implemented; these algorithms are based on integrating the current during the generation of silver ions, which makes it possible to provide a quantitative determination of chlorine content in the range from 1 to 60 μg/g. The proposed technical solutions ensure the reproducibility of results, ease of use, and the possibility of integrating the device into laboratory information systems.

This study focuses on the development of a comprehensive mathematical and computational model for a wireless battery charging system designed for autonomous underwater vehicles operating in seawater under rolling conditions. The research is motivated by the lack of existing models that account for the combined effects of varying coil alignment and the characteristics of a highly conductive medium. Experimental results are presented for a 150 W wireless charging system featuring a series LC topology intended for marine environments. The experiments aimed to validate the comprehensive mathematical and computational model—based on the mathematical description provided in the first part of the paper—and to assess the impact of the conductive medium (freshwater and seawater) on the system's energy characteristics. The experimental setup, utilizing multi-layer coils, and the measurement methodology are described. A comparative analysis was conducted between the system's amplitude-frequency characteristics in air, freshwater, and seawater and the corresponding simulation results. Parameters for the equivalent circuit, accounting for eddy current losses, are identified using a successive approximation method. It is demonstrated that model M2—which accounts for these losses via equivalent resistances—shows strong agreement with experimental data (with a root-mean-square error of no more than 5%), whereas the influence of parasitic capacitances within the 90–130 kHz operating frequency range is negligible. The study confirms the necessity of accounting for the nonlinearity of semiconductor components to accurately describe frequency-domain processes. The results validate the developed model and demonstrate its suitability for predicting system performance under actual operating conditions.

Methods and tools for organizing the computational process in embedded and specialized computing systems are discussed, with reference to a specific class of computational assistant mechanisms, for which a template of an invariant-variant design mechanism and a method for integrating it into the system architecture are proposed. The essence and effectiveness of the proposed abstractions and the architectural design method are demonstrated using a simple assistant mechanism as an example.