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Internet of Robotic Things (IoRT) and Metaheuristic Optimization Techniques Applied for Wheel-Legged Robot

Author

Listed:
  • Mateusz Malarczyk

    (Department of Electrical Machines, Drives and Measurements, Faculty of Electrical Engineering, Wroclaw University of Science and Technology, Smoluchowskiego 19, 50-372 Wroclaw, Poland)

  • Grzegorz Kaczmarczyk

    (Department of Electrical Machines, Drives and Measurements, Faculty of Electrical Engineering, Wroclaw University of Science and Technology, Smoluchowskiego 19, 50-372 Wroclaw, Poland)

  • Jaroslaw Szrek

    (Department of Fundamentals of Machine Design and Mechatronic Systems, Faculty of Mechanical Engineering, Wroclaw University of Science and Technology, Lukasiewicza 7/9, 50-372 Wroclaw, Poland)

  • Marcin Kaminski

    (Department of Electrical Machines, Drives and Measurements, Faculty of Electrical Engineering, Wroclaw University of Science and Technology, Smoluchowskiego 19, 50-372 Wroclaw, Poland)

Abstract

This paper presents the operation of a remotely controlled, wheel-legged robot. The developed Wi-Fi connection framework is established on a popular ARM microcontroller board. The implementation provides a low-cost solution that is in congruence with the newest industrial standards. Additionally, the problem of limb structure and motor speed control is solved. The design process of the mechanical structure is enhanced by a nature-inspired metaheuristic optimization algorithm. An FOC-based BLDC motor speed control strategy is selected to guarantee dynamic operation of the drive. The paper provides both the theoretical considerations and the obtained prototype experimental results.

Suggested Citation

  • Mateusz Malarczyk & Grzegorz Kaczmarczyk & Jaroslaw Szrek & Marcin Kaminski, 2023. "Internet of Robotic Things (IoRT) and Metaheuristic Optimization Techniques Applied for Wheel-Legged Robot," Future Internet, MDPI, vol. 15(9), pages 1-19, September.
  • Handle: RePEc:gam:jftint:v:15:y:2023:i:9:p:303-:d:1234016
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    References listed on IDEAS

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    1. Hegazy Rezk & A. G. Olabi & Tabbi Wilberforce & Enas Taha Sayed, 2023. "A Comprehensive Review and Application of Metaheuristics in Solving the Optimal Parameter Identification Problems," Sustainability, MDPI, vol. 15(7), pages 1-24, March.
    2. Hokey Min, 2023. "Smart Warehousing as a Wave of the Future," Logistics, MDPI, vol. 7(2), pages 1-12, May.
    3. Ahmed M. Nassef & Mohammad Ali Abdelkareem & Hussein M. Maghrabie & Ahmad Baroutaji, 2023. "Review of Metaheuristic Optimization Algorithms for Power Systems Problems," Sustainability, MDPI, vol. 15(12), pages 1-27, June.
    4. Yingqiang Wang & Dianxiang Zhang & Susanne S. Renner & Zhongyi Chen, 2004. "A new self-pollination mechanism," Nature, Nature, vol. 431(7004), pages 39-40, September.
    5. Mohamed Abdel-Basset & Reda Mohamed & Safaa Saber & S. S. Askar & Mohamed Abouhawwash, 2021. "Modified Flower Pollination Algorithm for Global Optimization," Mathematics, MDPI, vol. 9(14), pages 1-37, July.
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