Kybernetika a robotika

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    Utilizability of Navigation2/ROS2 in Highly Automated and Distributed Multi-Robotic Systems for Industrial Facilities
    (ELSEVIER, 2022-07-20) Horeličan, Tomáš
    The field of mobile robotics is a rapidly evolving space with a constant stream of new advancements. As the available technology matures and new features get accessible for lower prices, the scope of applicability for autonomous mobile robots naturally expands. Apart from simple home appliances, a particular area that currently attracts a surge of transformative research is that of industrial facilities and intelligent factories. A higher emphasis is gradually being placed on autonomous operations, where mobile robots start being suitable complements to human workers. Such an application, however, requires complex mechanisms to be able to handle even simple tasks, such as transferring cargo from one place to another while navigating a changing environment and avoiding dynamic obstacles. Robust localization and navigation solutions utilizing the most effective algorithms are necessary for such long and continuous operations that require a high degree of reliability and low error rates. Robot Operating System (ROS) is a highly flexible open-source framework enjoying wide adoption over the years. Its next-generation implementation (ROS2), together with the Navigation2 project (created as a successor to the original ROS Navigation Stack), provide substantial conceptual enhancements with a strong focus on reliability, security, and performance, promising better compatibility with numerous sensor types, higher modularity, and a more controllable deterministic behavior. This paper will guide the reader through necessary steps to deploy the Navigation2 stack onto an existing custom-built ROS2-operating robotic test-bed platform, serving as a concept for future research.
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    Vanishing and blow-up solutions to a class of nonlinear complex differential equations near the singular point
    (De Gruyter, 2024-02-05) Diblík, Josef; Růžičková, Miroslava
    A singular nonlinear differential equation z(sigma) dw/dz = aw + zwf(z , w), where sigma > 1, is considered in a neighbourhood of the point z = 0 z=0 located either in the complex plane C if sigma is a natural number, in a Riemann surface of a rational function if sigma is a rational number, or in the Riemann surface of logarithmic function if sigma is an irrational number. It is assumed that w = w ( z ) w=w\left(z) , a is an element of C { 0 } a, and that the function f f is analytic in a neighbourhood of the origin in C x C . Considering sigma to be an integer, a rational, or an irrational number, for each of the above-mentioned cases, the existence is proved of analytic solutions w = w (z ) w=w(z) in a domain that is part of a neighbourhood of the point z = 0 z=0 in C or in the Riemann surface of either a rational or a logarithmic function. Within this domain, the property lim z -> 0 w (z) = 0 is proved and an asymptotic behaviour of w (z) s established. Several examples and figures illustrate the results derived. The blow-up phenomenon is discussed as well.
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    Diagnostics of Interturn Short Circuits in PMSMs With Online Fault Indicators Estimation
    (IEEE, 2024-02-27) Zezula, Lukáš; Kozovský, Matúš; Blaha, Petr
    This article presents novel model-based diagnostics of interturn short circuits in permanent magnet synchronous machines that enable estimating fault location and its severity, even during transients. The proposed method utilizes recursive parametric estimation and model comparison approaches cast in a decision-making framework to track motor parameters and fault indicators from a machine's discrete-time model. The discrete-time prototype is derived from an advanced motor model that reflects the stator winding arrangement in a motor's case. The fault detection is then performed by tracking the changes in the estimated probability density function of the electrical parameters, using the Kullback–Leibler divergence. The fault location is subsequently evaluated by performing a recursive comparison of the predefined fault models in the different phases, utilizing a growing-window approach. Ultimately, a parametric estimation algorithm applied to the fault current model allows identifying the fault severity. The diagnostic algorithm has been validated via laboratory experiments, and its capabilities are compared with other approaches enabling severity estimation.
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    Capacity Building in Mathematics and Statistics Learning Support in Norway and the Czech Republic (MSLS Net)
    (sigma network, 2024-01-03) Rebenda, Josef; Pátíková, Zuzana; Chvátal, Martin; Rogovchenko, Svitlana; Bakke, Trris Kolen; Croft, Tony
    This report describes the final meeting of the project "Capacity Building in Mathematics and Statistics Learning Support in Norway and the Czech Republic (MSLS Net)" held at the Tomas Bata University in Zlín, Czech Republic (June 12-14, 2023). Provision of mathematics and statistics learning support (MSLS) is developing rapidly in many parts of the world and activity in Norway and the Czech Republic has been accelerated significantly through this EEA Grants funded project. Representatives of each of the five partner institutions worked on creating a summary of good practices in tutor training, designing learning resources, and in delivering, monitoring and evaluation of mathematics and statistics support. Provision varied considerably across the institutions and the centres represented demonstrated diverse and innovative ways in which mathematics support is evolving. Outputs from the project include a Handbook on good practice and a booklet concerned with mathematics support centre tutor training, including pedagogic training and learning resources for the development of the tutors as described below. Finally, consideration turned to the value of establishing a professional network to continue this important work. The report will be relevant to other international groups interested in working in university level mathematics and statistics support.
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    Robust perception systems for automated, connected, and electrified vehicles: advances from EU project ArchitectECA2030
    (Elsevier, 2023-12-13) Recekenzaun, Jakob; Solmaz, Selim; Goelles, Thomas; Hilbert, Marc; Weimer, Daniel; Mayer, Peter; Chromý, Adam; Hentschel, Uwe; Modler, Niels; Toth, Mate; Hennecke, Marcus
    The perception supply chain (SC1) of the ArchitectECA2030 project investigates failure modes, fault detection, and residual risk in perception systems of electrified, connected, and automated (ECA) vehicles. This accounts for the needs of a reliable understanding of the surrounding environment. The three demonstrators of SC1, described in this paper, address steps of a typical ECA usage cycle: charge - drive - restart charging. The foreign object detection (FOD) demonstrator improves safety within a wireless charging system. The robust physical sensors demonstrator creates a more robust perception by detecting failures within fused and single sensor data. The position enhancement demonstrator improves vehicle localization in areas with reduced GNSS signal coverage. All demonstrators are linked to the challenges that occur during the ECA vehicle usage cycle