Autonomous Multi-UAV Path Planning in Pipe Inspection Missions Based on Booby Behavior

Faten Aljalaud (), Heba Kurdi and Kamal Youcef-Toumi
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Faten Aljalaud: Computer Science Department, College of Computer and Information Sciences, King Saud University, Riyadh 11451, Saudi Arabia
Heba Kurdi: Computer Science Department, College of Computer and Information Sciences, King Saud University, Riyadh 11451, Saudi Arabia
Kamal Youcef-Toumi: Mechanical Engineering Department, Massachusetts Institute of Technology (MIT), Cambridge, MA 02139, USA

Mathematics, 2023, vol. 11, issue 9, 1-23

Abstract: This paper presents a novel path planning heuristic for multi-UAV pipe inspection missions inspired by the booby bird’s foraging behavior. The heuristic enables each UAV to find an optimal path that minimizes the detection time of defects in pipe networks while avoiding collisions with obstacles and other UAVs. The proposed method is compared with four existing path planning algorithms adapted for multi-UAV scenarios: ant colony optimization (ACO), particle swarm optimization (PSO), opportunistic coordination, and random schemes. The results show that the booby heuristic outperforms the other algorithms in terms of mean detection time and computational efficiency under different settings of defect complexity and number of UAVs.

Keywords: inspection; bio-inspired algorithms; unmanned aerial vehicle; booby; multi-UAV; path planning; pipes (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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