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

Author:

Romeh Ali El1ORCID,Mirjalili Seyedali123ORCID,Gul Faiza4

Affiliation:

1. Centre for Artificial Intelligence Research and Optimisation, Torrens University Australia, Brisbane 4006, Australia

2. Yonsei Frontier Lab, Yonsei University, Seoul 03722, Republic of Korea

3. University Research and Innovation Center, Obuda University, 1034 Budapest, Hungary

4. 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 (HVCME), which combines Coordinated Multi-Robot Exploration (CME) and African Vultures Optimization Algorithm (AVOA) to optimize the construction of a finite map in multi-robot exploration. We compared HVCME 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.

Publisher

MDPI AG

Subject

General Mathematics,Engineering (miscellaneous),Computer Science (miscellaneous)

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