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Investigation on the Mobile Wheeled Robot in Terms of Energy Consumption, Travelling Time and Path Matching Accuracy

Author

Listed:
  • Piotr Szeląg

    (Faculty of Electrical Engineering, Częstochowa University of Technology, 17 Armii Krajowej Avenue, 42-201 Częstochowa, Poland)

  • Sebastian Dudzik

    (Faculty of Electrical Engineering, Częstochowa University of Technology, 17 Armii Krajowej Avenue, 42-201 Częstochowa, Poland)

  • Anna Podsiedlik

    (Faculty of Electrical Engineering, Częstochowa University of Technology, 17 Armii Krajowej Avenue, 42-201 Częstochowa, Poland)

Abstract

The task of controlling a wheeled mobile robot is an important element of navigation algorithms. The control algorithm manages the robot’s movement in accordance with the path determined by the planner module, where the accuracy of mapping the given route is very important. Most often, mobile robots are battery-powered, which makes minimizing energy consumption and shortening travel time an important issue. For this reason, in this work, the mobile robot control algorithm was tested in terms of energy consumption, travel time and path mapping accuracy. During the research, a criterion was developed, thanks to which it was possible to select the optimal parameters of the pure pursuit algorithm that controls the movement of the tested robot. The research was carried out in the Laboratory of Intelligent Mobile Robots using the QBot2e mobile robot operating on the basis of differential drive kinematics. As a result of the research, optimal values of the control parameters were obtained, minimizing the travel time, energy consumption and mapping error of the given paths.

Suggested Citation

  • Piotr Szeląg & Sebastian Dudzik & Anna Podsiedlik, 2023. "Investigation on the Mobile Wheeled Robot in Terms of Energy Consumption, Travelling Time and Path Matching Accuracy," Energies, MDPI, vol. 16(3), pages 1-30, January.
    • Handle: RePEc:gam:jeners:v:16:y:2023:i:3:p:1210-:d:1043968
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    References listed on IDEAS

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    1. Kazuki Nonoyama & Ziang Liu & Tomofumi Fujiwara & Md Moktadir Alam & Tatsushi Nishi, 2022. "Energy-Efficient Robot Configuration and Motion Planning Using Genetic Algorithm and Particle Swarm Optimization," Energies, MDPI, vol. 15(6), pages 1-20, March.
    2. Dariusz Horla & Jacek Cieślak, 2020. "On Obtaining Energy-Optimal Trajectories for Landing of UAVs," Energies, MDPI, vol. 13(8), pages 1-25, April.
    3. Liu, Yang & Zhang, Qi & Lyu, Cheng & Liu, Zhiyuan, 2021. "Modelling the energy consumption of electric vehicles under uncertain and small data conditions," Transportation Research Part A: Policy and Practice, Elsevier, vol. 154(C), pages 313-328.
    4. Sebastian Dudzik, 2020. "Application of the Motion Capture System to Estimate the Accuracy of a Wheeled Mobile Robot Localization," Energies, MDPI, vol. 13(23), pages 1-29, December.
    Full references (including those not matched with items on IDEAS)

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