{"id":6705,"date":"2026-02-22T22:10:51","date_gmt":"2026-02-22T22:10:51","guid":{"rendered":"https:\/\/izvestiyakbncran.ru\/?page_id=6705"},"modified":"2026-05-15T11:25:57","modified_gmt":"2026-05-15T10:25:57","slug":"28-1-7-en","status":"publish","type":"page","link":"https:\/\/izvestiyakbncran.ru\/index.php\/en\/28-1-7-en\/","title":{"rendered":"28.1.7 En"},"content":{"rendered":"\n

Architecture for two-level mobile robot control system for warehouse logistics<\/strong><\/h1>\n\n\n\n

V.V. Shukhin, Z.L. Khakimov, M. A. Labazanov<\/strong><\/p>\n\n\n\n

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Abstract<\/strong>.<\/strong> <\/em>The relevance of this work is driven by the growth of the warehouse robotics market and the need to combine intelligent functions with precise, deterministic control. A two-tier architecture for an autonomous mobile robot control system is proposed, separating cognitive (NVIDIA Jetson Orin Nano, ROS 2) and executive (STM32H743ZI, FreeRTOS) functions. A specialized data exchange protocol with integrity monitoring is developed. The proposed architecture ensures balanced distribution of the computational load and can be used to create high-precision mobile platforms for warehouse applications.
Aim<\/strong>. The research is to develop and mathematically justify such an architecture, evaluate its ultimate performance, and demonstrate its advantages through a comparative analysis with existing approaches.
Research methods<\/strong>. The following research methods are used in this study:<\/p>\n\n\n\n

1. Mathematical modeling and calculations \u2013 formalization of models for assessing positioning accuracy using an extended Kalman filter, calculation of system timing parameters, and the probability of data transmission errors. <\/p>\n\n\n\n

2. Simulation modeling \u2013 system verification in ROS 2 and Gazebo, assessment of dynamic accuracy and response time.<\/p>\n\n\n\n

3. Algorithmic design \u2013 development of cascade PID controllers for motor control and an exchange protocol between architecture levels.<\/p>\n\n\n\n

4. Comparative analysis \u2013 comparison of the characteristics of the proposed system with commercial analogues (MiR250, Fetch Freight 1500).<\/p>\n\n\n\n

5. Experimental evaluation \u2013 Monte Carlo simulation to determine the root mean square positioning error, energy consumption and autonomy analysis.
Results<\/strong>. This paper presents an innovative two-tier architecture for an autonomous mobile robot (AMR) control system for warehouse logistics. The architecture divides the computational load between a high-level controller based on a NVIDIA Jetson Orin Nano single-board computer (4 GB) running the ROS 2 Humble operating system and a low-level controller based on an STM32H743ZI microprocessor (ARM Cortex-M7 core, 550 MHz) running the FreeRTOS RTOS. The high-level controller handles navigation using SLAM algorithms (based on the Ouster OS0-32 lidar) and global path planning, while the low-level controller provides precision motor control via cascaded PID controllers and data processing from Renishaw RESOLUTE absolute encoders with 26-bit resolution. This paper presents the developed binary communication protocol with integrity checking (CRC-16-CCITT), formalizes mathematical models for calculating positioning accuracy, and identifies critical timing parameters of the system. The estimated low-level control cycle time is 1 ms, and the average interprocess communication latency is 3.5 ms. The system demonstrates a theoretical positioning accuracy of \u00b12.1 mm using odometry and lidar sensor fusion. Simulation results indicate the feasibility of processing up to 15 target tasks per minute in a typical 10×10 m warehouse cell.
Conclusion<\/strong>. The proposed architecture represents a balanced solution combining high performance, determinism, and relative affordability, making it a promising foundation for the next generation of research and commercial warehouse AMRs.<\/p>\n\n\n\n

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Keywords<\/strong>:<\/em><\/strong> autonomous mobile robot, warehouse logistics, distributed control system, ROS 2, FreeRTOS, sensor fusion, PID controller, absolute encoders<\/p>\n\n\n\n

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For citation<\/strong>.<\/strong> Shukhin V.V., Khakimov Z.L., Labazanov M.A. Architecture for two-level mobile robot control system for warehouse logistics. News of the Kabardino-Balkarian Scientific Center of RAS. 2026. Vol. 28. No. 1. Pp. 102\u2013116. DOI: 10.35330\/1991-6639-2026-28-1-102-116<\/p>\n\n\n\n

\u00a9   Shukhin V.V., Khakimov Z.L., Labazanov M.A., 2026<\/p>\n\n\n\n

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Content is available under license Creative Commons Attribution 4.0 License<\/a><\/p>\n<\/div>\n\n\n\n

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R<\/strong>eferences<\/summary>\n
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  2. Uglovsky A.S. Motion control system of a mobile robot. Bulletin of the Agroindustrial Complex of the Upper Volga Region. 2024. \u2116 2(66). Pp. 98\u2013108. DOI: 10.35694\/YARCX.2024.66.2.013. EDN: WFPSEJ. (In Russian)<\/li>\n\n\n\n
  3. Kutafin A.A., Zakharkina S.V. Motor control in a mobile robot using a PID controller. Innovative Development of Machinery and Technologies in Industry (INTEX-2021): Proceedings Of The All-Russian Scientific Conference of Young Researchers with International Participation, Moscow, April 12\u201315, 2021. Volume Part 4. Moscow: Federal State Budgetary Educational Institution of Higher Education \u201cA.N. Kosygin Russian State University (Technology. Design. Art)\u201d, 2021. Pp. 208\u2013212. EDN: XKLAGG. (In Russian)<\/li>\n\n\n\n
  4. Kraev R.V., Belozerskikh V.V. SLAM concept for optimizing the model ofsoftware control of robot movement on a map with control points. High-Performance Computing Systems and Technologies. 2020. Vol. 4. No. 2. Pp. 59\u201365. EDN: JRQBHN. (In Russian)<\/li>\n\n\n\n
  5. Berkaev A.R., Nenashev A.A., Klyuchikov A.V. Development of a mobile localization and positioning system. Mathematical Methods in Engineering and Technology \u2013 MMTT. 2020. Vol. 12-3. Pp. 152\u2013157. EDN: QDGESL. (In Russian)<\/li>\n\n\n\n
  6. Guo P., Shi H., Wang Sh. et al. An ROS architecture for autonomous mobile robots with UCAR platforms in smart restaurants. Machines. MDPI AG \u2013 2022. Vol. 10. No. 10. P. 844. DOI: 10.3390\/machines10100844. EDN: ADSREE<\/li>\n\n\n\n
  7. Alkhalili A.S., Lukyanov E.A. Motion control of a wheeled mobile robot based on simulation modeling. Bulletin of BSTU named after V.G. Shukhov. 2022. No. 8. Pp. 112\u2013121. EDN: XJSZPY. (In Russian)<\/li>\n\n\n\n
  8. Lapshinov S.A., Shakhnov V.A., Yudin A.V. Directions of intellectualization of motion control of a mobile robot. Neurocomputers: Development, Application. 2021. Vol. 23. No. 1. Pp. 50\u201362. EDN: FKKKGV. (In Russian)<\/li>\n\n\n\n
  9. Bezmen P.A. Kalman filter algorithm for data aggregation in a mobile robot control system. Fundamental and Applied Problems of Engineering and Technology. 2019. \u2116 3(335). Pp. 82\u201387. EDN: AYKMKS. (In Russian)<\/li>\n\n\n\n
  10. Deshmukh A., Gupta M. PID Controller: a review of literature. International Journal of Scientific Research in Computer Science, Engineering and Information Technology (IJSRCSEIT). Vol. 6. Is. 3. Pp. 48\u201353. DOI: 10.32628\/IJSRCSEIT.0639<\/li>\n\n\n\n
  11. Shahbazi M. Machine learning-based approaches for obstacle detection and avoidance in autonomous vehicles: A review. Expert Systems with Applications. 2021. 172:114535. DOI: 10.1016\/j.eswa.2021.114535<\/li>\n\n\n\n
  12. Malov D.A., Edemsky A.Yu., Savelyev A.I. Development of a system for proactive localization of cyberphysical space based on machine learning methods. Information Technologies and Computing Systems. 2018. No. 4. Pp. 72\u201383. DOI: 10.14357\/20718632180408. EDN: MIDRAT. (In Russian)<\/li>\n\n\n\n
  13. Gorkavyy M.A., Gorkavyy A.I., Melnichenko M.A. Optimization of a robotic technological process based on a neural network simulation model of energy consumption. Izvestia of Higher Educational Institutions. Electromechanics. 2023. Vol. 66. No. 2. Pp. 85\u201395. DOI: 10.17213\/0136-3360-2023-2-85-95. EDN: WYKEWQ. (In Russian)<\/li>\n\n\n\n
  14. Lopota A.V., Spassky B.A. Mobile ground-based robotic complexes for professional use. Robotics and Technical Cybernetics. 2020. Vol. 8, No. 1. Pp. 5\u201317. DOI: 10.31776\/RTCJ.8101. EDN: JAQTQG. (In Russian)<\/li>\n\n\n\n
  15. Veselov G.E., Lebedev B.K., Lebedev O.B. Motion control of a group of mobile robots in a column. Informatization and Communications. 2021. No. 3. Pp. 7\u201311. DOI: 10.34219\/2078-8320-2021-12-3-7-11. EDN: LDISYZ. (In Russian)<\/li>\n<\/ol>\n<\/details>\n\n\n\n
    Information about the author<\/strong>s<\/summary>\n
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    Vladimir V. Shukhin<\/strong>, Candidate of Technical Sciences, Associate Professor, Department of Automation of Technological Processes and Production, Grozny State Oil Technical University named after academician M.D. Millionshchikov;
    100, Isaev avenue, Grozny, 364051, Russia;
    shukhin86@bk.ru, ORCID: https:\/\/orcid.org\/0009-0003-0273-0058, SPIN-code: 2895-3434
    Zaur L. Khakimov<\/strong>, Candidate of Technical Sciences, Associate Professor, Department of Automation of Technological Processes and Production, Grozny State Oil Technical University named after academician M.D. Millionshchikov;
    100, Isaev avenue, Grozny, 364051, Russia;
    deffender_95@mail.ru, ORCID: https:\/\/orcid.org\/0009-0007-1665-8631, SPIN-code: 3540-6580
    Magomed A. Labazanov<\/strong>, Senior Lecturer, Department of Automation of Technological Processes and Production, Grozny State Oil Technical University named after academician M.D. Millionshchikov;
    100, Isaev avenue, Grozny, 364051, Russia;
    labazanov.90@inbox.ru, ORCID: https:\/\/orcid.org\/0009-0005-9714-5146, SPIN-code: 5981-5217<\/p>\n\n\n\n

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    Funding<\/strong><\/summary>\n

    The study was performed without external funding.<\/p>\n<\/details>\n\n\n\n

    <\/p>\n","protected":false},"excerpt":{"rendered":"

    Architecture for two-level mobile robot control system for warehouse logistics V.V. Shukhin, Z.L. Khakimov, M. A. Labazanov Abstract. The relevance of this work is driven by the growth of the warehouse robotics market and the need to combine intelligent functions with precise, deterministic control. A two-tier architecture for an autonomous mobile robot control system is […]<\/p>\n","protected":false},"author":1,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"wp-custom-template-home","meta":{"footnotes":""},"class_list":["post-6705","page","type-page","status-publish","hentry"],"yoast_head":"\n28.1.7 En - \u0418\u0417\u0412\u0415\u0421\u0422\u0418\u042f \u041a\u0410\u0411\u0410\u0420\u0414\u0418\u041d\u041e-\u0411\u0410\u041b\u041a\u0410\u0420\u0421\u041a\u041e\u0413\u041e \u041d\u0410\u0423\u0427\u041d\u041e\u0413\u041e \u0426\u0415\u041d\u0422\u0420\u0410 \u0420\u0410\u041d\u00bb<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/izvestiyakbncran.ru\/index.php\/en\/28-1-7-en\/\" \/>\n<meta property=\"og:locale\" content=\"ru_RU\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"28.1.7 En - \u0418\u0417\u0412\u0415\u0421\u0422\u0418\u042f \u041a\u0410\u0411\u0410\u0420\u0414\u0418\u041d\u041e-\u0411\u0410\u041b\u041a\u0410\u0420\u0421\u041a\u041e\u0413\u041e \u041d\u0410\u0423\u0427\u041d\u041e\u0413\u041e \u0426\u0415\u041d\u0422\u0420\u0410 \u0420\u0410\u041d\u00bb\" \/>\n<meta property=\"og:description\" content=\"Architecture for two-level mobile robot control system for warehouse logistics V.V. Shukhin, Z.L. Khakimov, M. A. Labazanov Abstract. The relevance of this work is driven by the growth of the warehouse robotics market and the need to combine intelligent functions with precise, deterministic control. 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Shukhin, Z.L. Khakimov, M. A. Labazanov Abstract. The relevance of this work is driven by the growth of the warehouse robotics market and the need to combine intelligent functions with precise, deterministic control. 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