Modeling and Control of Robotic Systems

A special issue of Mathematics (ISSN 2227-7390). This special issue belongs to the section "Engineering Mathematics".

Deadline for manuscript submissions: closed (30 June 2024) | Viewed by 1433

Special Issue Editors


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Guest Editor
Department of Industrial Automation, University of Chemical Technology and Metallurgy, 8 Kliment Ohridski blvd, 1756 Sofia, Bulgaria
Interests: industrial automation and control; industrial informatics; modeling; simulation and optimization; cyber–physical systems; intelligent manufacturing systems; machine learning; system engineering; software engineering

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Guest Editor
1. Department of Industrial Automation, University of Chemical Technology and Metallurgy, 8 Kliment Ohridski blvd, 1756 Sofia, Bulgaria
2. Institute of Electronics, Bulgarian Academy of Sciences, 72 Tzarigradsko shossee blvd., 1784 Sofia, Bulgaria
Interests: industrial automation; analytical and empirical modeling; simulation and optimization; intelligent methods for data analysis; industrial process control; quality control; statistics; experimental design; neural networks; robust engineering; the IoT and WSN; smart cities; electron beam technologies; additive manufacturing
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Special Issue Information

Dear Colleagues,

Robotic systems are complex dynamic systems, and their modeling as well as simulation are fundamental for solving many tasks related to the phases of their design, verification, testing, implementation, planning, control, maintenance, security, and evaluation. All of this poses great challenges to the development of methods and tools for the modeling and simulation of robotic systems. Addressing these challenges is related to the creation of modern mathematical foundations for modeling and simulation, covering different aspects and perspectives of robotic systems of different types in addition to supporting the development and operation of efficient, flexible, resilient, secure, precise, accurate, autonomous, and interoperable robotics systems.

This Special Issue collects papers with the aim of presenting some of the latest achievements in the fields of the development, analysis, and application of advanced mathematical methods for the modeling and simulation of various types of robotics systems—manipulation, mobile, data acquisition, and control robotic systems. Particularly relevant are papers that present hybrid solutions in the fields of building the theoretical foundations and practical implementations of cyber–physical systems (such as robotic systems), as well as the related digital twins. Preference will be given to papers that offer sustainable and efficient solutions in the fields of the modeling and simulation of various aspects of robotics systems as well as their elements and that can be used in different phases of their life cycle, such as analysis, design, implementation, operation, and maintenance.

Dr. Idilia Batchkova
Dr. Elena Koleva
Guest Editors

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Keywords

  • mathematical modeling and simulation
  • cyber–physical systems
  • digital twins
  • machine learning
  • knowledge modeling
  • autonomous systems
  • formal methods
  • formal verification and validation
  • fuzzy modeling

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Published Papers (1 paper)

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Research

16 pages, 6921 KiB  
Article
Path Planning of Logistic Robot Using Method of Vector Marks Tree Generation
by Olga Strikuliene, Kastytis Kiprijonas Sarkauskas, Julius Gelsvartas, Leonas Balasevicius, Virginijus Baranauskas and Alma Derviniene
Mathematics 2024, 12(1), 73; https://doi.org/10.3390/math12010073 - 25 Dec 2023
Viewed by 822
Abstract
The authors of this article analyzed the problem of logistic robotics. This paper presents a method for robot navigation in a known environment. The method consists of two steps. The first step is to model the system, assign vector marks to the prominent [...] Read more.
The authors of this article analyzed the problem of logistic robotics. This paper presents a method for robot navigation in a known environment. The method consists of two steps. The first step is to model the system, assign vector marks to the prominent edges of the virtual environment map, and direct the robot to reach these marks. The second step is to enable the robot to execute a specific task based on the given paths and deal with the local obstacles avoidance independently. The identification of the prominent point, the computation of the vector mark, and optimal path calculation are performed on the computer model using colored Petri nets in the software ‘Centaurus CPN’. The proposed approach was extended to simulate the work of a logistic robot, which has to take boxes and deliver them to certain places in storages. The experimental investigation has shown that the simulated mobile robots with the proposed navigation system were efficiently moving along the planned path. The analysis of the vector tree reveals that it takes 0.389 s to compute and graphically represent it. The occupation of certain places in storages is visualized and shown in experimental graphics. Full article
(This article belongs to the Special Issue Modeling and Control of Robotic Systems)
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