Autonomous Multi-UAV Path Planning in Pipe Inspection Missions Based on Booby Behavior
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mathematics-11-02092.pdf
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4.57 MB
Format
Adobe PDF
Checksum (MD5)
30515547ca5ff7f92948f172f5277dc3
Author(s)
Aljalaud, Faten
Kurdi, Heba
Youcef-Toumi, Kamal
Date Issued
April 28, 2023
Publisher
Multidisciplinary Digital Publishing Institute
Citation
Mathematics 11 (9): 2092 (2023)
Version
Final published version
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.
MIT Department
Massachusetts Institute of Technology. Department of Mechanical Engineering
Terms of Use
Creative Commons Attribution
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.3390/math11092092
