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An Investigation into the Energy-Efficient Motion of Autonomous Wheeled Mobile Robots

Author

Listed:
  • Mohammad Mohammadpour

    (Department of Mechanical Engineering, University of Quebec at Trois-Rivieres, Trois-Rivieres, QC G8Z 4M3, Canada)

  • Lotfi Zeghmi

    (Department of Electrical and Computer Engineering, University of Quebec at Trois-Rivieres, Trois-Rivieres, QC G8Z 4M3, Canada)

  • Sousso Kelouwani

    (Department of Mechanical Engineering, University of Quebec at Trois-Rivieres, Trois-Rivieres, QC G8Z 4M3, Canada)

  • Marc-André Gaudreau

    (Department of Mechanical Engineering, University of Quebec at Trois-Rivieres, Trois-Rivieres, QC G8Z 4M3, Canada)

  • Ali Amamou

    (Department of Electrical and Computer Engineering, University of Quebec at Trois-Rivieres, Trois-Rivieres, QC G8Z 4M3, Canada)

  • Massinissa Graba

    (Department of Electrical and Computer Engineering, University of Quebec at Trois-Rivieres, Trois-Rivieres, QC G8Z 4M3, Canada)

Abstract

In recent years, the use of electric Autonomous Wheeled Mobile Robots (AWMRs) has dramatically increased in transport of the production chain. Generally, AWMRs must operate for several hours on a single battery charge. Since the energy density of the battery is limited, energy efficiency becomes a key element in improving material transportation performance during the manufacturing process. However, energy consumption is influenced by the navigation stages, because the type of motion necessary for the AWMR to perform during a mission is totally defined by these stages. Therefore, this paper analyzes methods of energy efficiency that have been studied recently for AWMR navigation stages. The selected publications are classified into planning and motion control categories in order to identify research gaps. Unlike other similar studies, this work focuses on these methods with respect to their implications for the energy consumption of AWMRs. In addition, by using an industrial Self-Guided Vehicle (SGV), we illustrate the direct influence of the motion planning stage on global energy consumption by means of several simulations and experiments. The results indicate that the reaction of the SGV in response to unforeseen obstacles can affect the amount of energy consumed. Hence, energy constraints must be considered when developing the motion planning of AWMRs.

Suggested Citation

  • Mohammad Mohammadpour & Lotfi Zeghmi & Sousso Kelouwani & Marc-André Gaudreau & Ali Amamou & Massinissa Graba, 2021. "An Investigation into the Energy-Efficient Motion of Autonomous Wheeled Mobile Robots," Energies, MDPI, vol. 14(12), pages 1-19, June.
  • Handle: RePEc:gam:jeners:v:14:y:2021:i:12:p:3517-:d:574294
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    References listed on IDEAS

    as
    1. Yina Wang & Wenqiu Xiong & Junyou Yang & Yinlai Jiang & Shuoyu Wang, 2019. "A Robust Feedback Path Tracking Control Algorithm for an Indoor Carrier Robot Considering Energy Optimization," Energies, MDPI, vol. 12(10), pages 1-23, May.
    2. Massinissa Graba & Sousso Kelouwani & Lotfi Zeghmi & Ali Amamou & Kodjo Agbossou & Mohammad Mohammadpour, 2020. "Investigating the Impact of Energy Source Level on the Self-Guided Vehicle System Performances, in the Industry 4.0 Context," Sustainability, MDPI, vol. 12(20), pages 1-21, October.
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    Cited by:

    1. Łukasz Gruszka & Michał Bartyś, 2022. "A New Energy-Efficient Approach to Planning Pick-and-Place Operations," Energies, MDPI, vol. 15(23), pages 1-27, November.
    2. Deniss Stepins & Aleksandrs Sokolovs & Janis Zakis & Ouseph Charles, 2023. "Wireless Battery Chargers Operating at Multiple Switching Frequencies with Improved Performance," Energies, MDPI, vol. 16(9), pages 1-18, April.

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