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Hybrid Vulture-Coordinated Multi-Robot Exploration: A Novel Algorithm for Optimization of Multi-Robot Exploration

Author

Listed:
  • Ali El Romeh

    (Centre for Artificial Intelligence Research and Optimisation, Torrens University Australia, Brisbane 4006, Australia)

  • Seyedali Mirjalili

    (Centre for Artificial Intelligence Research and Optimisation, Torrens University Australia, Brisbane 4006, Australia
    Yonsei Frontier Lab, Yonsei University, Seoul 03722, Republic of Korea
    University Research and Innovation Center, Obuda University, 1034 Budapest, Hungary)

  • Faiza Gul

    (Department of Electrical Engineering, Air University, Aerospace & Aviation Campus KAMRA, Islamabad 43600, Pakistan)

Abstract

Exploring unknown environments using multiple robots has numerous applications in various fields but remains a challenging task. This study proposes a novel hybrid optimization method called Hybrid Vulture-Coordinated Multi-Robot Exploration ( H V C M E ), which combines Coordinated Multi-Robot Exploration ( C M E ) and African Vultures Optimization Algorithm ( A V O A ) to optimize the construction of a finite map in multi-robot exploration. We compared H V C M E with four other similar algorithms using three performance measures: run time, percentage of the explored area, and the number of times the method failed to complete a run. The experimental results show that HVCME outperforms the other four methods, demonstrating its effectiveness in optimizing the construction of a finite map in an unknown indoor environment.

Suggested Citation

  • Ali El Romeh & Seyedali Mirjalili & Faiza Gul, 2023. "Hybrid Vulture-Coordinated Multi-Robot Exploration: A Novel Algorithm for Optimization of Multi-Robot Exploration," Mathematics, MDPI, vol. 11(11), pages 1-30, May.
    • Handle: RePEc:gam:jmathe:v:11:y:2023:i:11:p:2474-:d:1157551
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    Cited by:

    1. Ali El Romeh & Seyedali Mirjalili, 2023. "Theoretical Framework and Practical Considerations for Achieving Superior Multi-Robot Exploration: Hybrid Cheetah Optimization with Intelligent Initial Configurations," Mathematics, MDPI, vol. 11(20), pages 1-33, October.

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