Test Model of a Warehouse Loader Robot for Situational Control Analysis System

  • Andrey Yu. KuchminEmail author
Part of the Studies in Systems, Decision and Control book series (SSDC, volume 261)


Introduction: In the modern world, more and more tasks are performed by robotic systems with artificial intelligence. Of great interest is the creation of control systems for distributed groups of robots when operating under conditions of non-stationarity of the external environment and interaction of robots, as well as insufficient information about the situations that arise. One of the most promising directions for the synthesis of such systems is the use of situational control methods. Modern intellectual systems calculate control actions taking into account forecasting, using adequate models of control objects. The development of such models should meet the following criteria. Such a model should adequately describe the behavior of the control object, should be compact and economical in terms of computation, since such models are repeatedly used to predict in one iteration of the control calculation cycle. Testing and analysis of situational control systems are important tasks that are often solved by simulation methods using control object models. Therefore, the development and analysis of situational control systems of groups of robots and the creation of adequate models of the dynamics and kinematics of these robots are actual. Purpose: To develop a simplified kinematic and dynamic model of a warehouse loader robot for use in the analysis system of situational control of a group of robots. Methods: Creating a library of modules based on object-oriented modeling methods. The library allows you to simulate the kinematics and dynamics of various configurations of robots based on intelligent electromechanical modules with a parallel kinematic scheme (SEMS). Results: Kinematic and dynamic models of a warehouse loader robot created from modules with parallel kinematic scheme (SEMS) are proposed. The robot is equipped with two universal adaptive grips that simulate human hands. These models can be used to calculate the trajectories of the robots and calculate the movements of universal adaptive grippers. These models can be used as virtual robots for testing situational control systems of a group of robots. Practical significance: The research results are supposed to be used in the development of test equipment of situational control systems for a group of robots.


SEMS Warehouse loader robot Situational control Model Dynamics Kinematics 



This work was financially supported by Russian Foundation for Basic Research, Grant 19-08-00079.


  1. 1.
    Bonkenburg, T.: Robotics in Logistics. A DPDHL Perspective on Implications and Use Cases for the Logistics Industry, Mar 2016. July 04, 2019
  2. 2.
    McCrea, B.: Mobility & Robotics in the Warehouse. Modern Materials Handling, 96 p., Mar 2016Google Scholar
  3. 3.
    Ackerman Warehousing Forum, vol. 31, no. 5, April 2016. July 04, 2019
  4. 4.
    Scassellati, B., Tsui, K.M.: Co-Robots: Humans and Robots Operating as Partners. Handbook of Science and Technology Convergence. Springer International Publishing Switzerland (2015). July 04, 2019Google Scholar
  5. 5.
    Gorodetskiy, A.E. (ed.): Smart Electromechanical Systems, 277 p. Springer International Publishing Switzerland (2016)Google Scholar
  6. 6.
    Gorodetskiy, A.E., Kurbanov, V.G. (eds.): Smart Electromechanical Systems: The Central Nervous System, 266 p. Springer International Publishing AG (2017)Google Scholar
  7. 7.
    Volkomorov, S.V., Kaganov, Yu.T., Karpenko, A.P.: Modelling and Optimization of Some Parallel Mechanisms, 32 p. New Technologies, Moscow (2010). (in Russian)Google Scholar
  8. 8.
    Glazunov, V.A., Koliskor, A.Sh., Kraynev, A.F.: Spatial Mechanisms of Parallel Structure, 96 p. Science, Moscow (1991). (in Russian)Google Scholar
  9. 9.
    Zenkevich, S.L., Yushchenko, A.S.: Bases of Control of Handling Robots, 480 p. MSTU, Moscow (2004). (in Russian)Google Scholar
  10. 10.
    Merlet, J.P.: Parallel Robots (Solid Mechanics and Its Applications). Springer, Berlin (2004)Google Scholar
  11. 11.
    Heylo, S.V., Glazunov, V.A., Palochkin, S.V.: Handling Mechanisms of Parallel Structure. The Dynamic Analysis and Management, 86 p. MGUDT, Moscow (2014). (in Russian)Google Scholar
  12. 12.
    Agapov, V.A., Gorodetsky, A.E., Kuchmin, A.Yu., Selivanova, E.N.: Medical microrobot. Patent for the Invention of RUS 2469752 5/20/2011. (in Russian)Google Scholar
  13. 13.
    Gorodetskij, A.E., Kurbanov, V.G., Tarasova, I.L.: Adaptive gripping device. Patent for the Invention of RUS 2624278 C1, July 12, 2016. (in Russian). July 04, 2019
  14. 14.
    Kuchmin, A.Yu., Dubarenko, V.V.: Linearized model of the mechanism with parallel structure. In: Gorodetskiy, A.E., Kurbanov, V.G. (eds.) Smart Electromechanical Systems: The Central Nervous System, 266 p. Springer International Publishing AG (2017). Scholar
  15. 15.
    Artemenko, Yu.N., Agapov, V.A., Dubarenko, V.V., Kuchmin, A.Yu.: Co-operative control of subdish actuators of radio telescope. Informatsionno-upravliaiushchie sistemy 4, 2–9 (2012). (in Russian)Google Scholar
  16. 16.
    Isermann, R., Münchhof, M.: Identification of Dynamic Systems. An Introduction with Applications, 705 p. Springer (2011)Google Scholar
  17. 17.
    Mzyk, G.: Combined Parametric-Nonparametric Identification of Block-Oriented Systems, 238 p. Springer (2014)Google Scholar
  18. 18.
    Boutalis, Y., Theodoridis, D., Kottas, T., Christodoulou, M.A.: System Identification and Adaptive Control. Theory and Applications of the Neurofuzzy and Fuzzy Cognitive Network Models, 313 p. Springer (2014)Google Scholar
  19. 19.
    Grop, D.: Methods of Identification Systems, 302 p. Springer-Verlag (1979)Google Scholar
  20. 20.
    Karabutov, N.N.: Strukturnaia identifikatsiia sistem: Analiz dinamicheskikh struktur [Structural Identification of Systems: Analysis of Dynamic Structures], 160 p. MGIU, Moscow (2008). (in Russian)Google Scholar
  21. 21.
    Kuchmin, A.Yu.: Identification of dynamics of modules SEMS. In: Gorodetskiy, A.E., Tarasova, I.L. (eds.) Smart Electromechanical Systems. Group Interaction, pp. 193–202. Springer Nature Switzerland AG (2019). Scholar
  22. 22.
    Kuchmin, A.Yu., Dubarenko, V.V.: Definition of a rigidity of a hexapod. In: Gorodetskiy, A.E. (ed.) Smart Electromechanical Systems, 277 p. Springer International Publishing Switzerland (2016)Google Scholar

Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.Institute of Problems of Mechanical Engineering, Russian Academy of SciencesSt. PetersburgRussia

Personalised recommendations