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Energy Consumption Analysis of the Selected Navigation Algorithms for Wheeled Mobile Robots

Author

Listed:
  • Adam Rapalski

    (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)

Abstract

The article presents the research on navigation algorithms of a wheeled mobile robot with the use of a vision mapping system and the analysis of energy consumption of selected navigation algorithms, such as RRT and A-star. Obstacle maps were made with the use of an RGBW camera, and binary occupation maps were also made, which were used to determine the traffic path. To recreate the routes in hardware, a programmed Pure Pursuit controller was used. The results of navigation were compared on the basis of the forward kinematics model and odometry measurements. Quantities such as current, except (x, y, phi), and linear and angular velocities were measured in real time. As a result of the conducted research, it was found that the RRT star algorithm consumes the least energy to reach the designated target in the designated environment.

Suggested Citation

  • Adam Rapalski & Sebastian Dudzik, 2023. "Energy Consumption Analysis of the Selected Navigation Algorithms for Wheeled Mobile Robots," Energies, MDPI, vol. 16(3), pages 1-37, February.
    • Handle: RePEc:gam:jeners:v:16:y:2023:i:3:p:1532-:d:1057355
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    References listed on IDEAS

    as
    1. Krystian Góra & Mateusz Kujawinski & Damian Wroński & Grzegorz Granosik, 2021. "Comparison of Energy Prediction Algorithms for Differential and Skid-Steer Drive Mobile Robots on Different Ground Surfaces," Energies, MDPI, vol. 14(20), pages 1-16, October.
    2. 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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    Cited by:

    1. Sathian Pookkuttath & Prabakaran Veerajagadheswar & Mohan Rajesh Elara, 2023. "AI-Enabled Condition Monitoring Framework for Indoor Mobile Cleaning Robots," Mathematics, MDPI, vol. 11(17), pages 1-21, August.
    2. Sathian Pookkuttath & Raihan Enjikalayil Abdulkader & Mohan Rajesh Elara & Prabakaran Veerajagadheswar, 2023. "AI-Enabled Vibrotactile Feedback-Based Condition Monitoring Framework for Outdoor Mobile Robots," Mathematics, MDPI, vol. 11(18), pages 1-23, September.
    3. Krystian Góra & Grzegorz Granosik & Bartłomiej Cybulski, 2024. "Energy Utilization Prediction Techniques for Heterogeneous Mobile Robots: A Review," Energies, MDPI, vol. 17(13), pages 1-17, July.

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    1. 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.

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