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

Ali El Romeh, Seyedali Mirjalili () and Faiza Gul
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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
Faiza Gul: Department of Electrical Engineering, Air University, Aerospace & Aviation Campus KAMRA, Islamabad 43600, Pakistan

Mathematics, 2023, vol. 11, issue 11, 1-30

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.

Keywords: Hybrid Vulture-Coordinated Multi-Robot Exploration (HVCME); optimization; African Vulture Optimization Algorithm (AVOA); multi-robot exploration; finite map; Coordinated Multi-Robot Exploration (CME); unknown environments; path planning (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2023
References: View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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