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Task Allocation Optimization for Multi-UAV Collaborative Power Inspection at Single Parking Point
Author(s) -
Zhuang Liu,
Huanqing Cai,
Guiwei Shao,
Ning Yang,
Zhike Wen,
Liwei Zhou
Publication year - 2025
Publication title -
ieee access
Language(s) - English
Resource type - Magazines
SCImago Journal Rank - 0.587
H-Index - 127
eISSN - 2169-3536
DOI - 10.1109/access.2025.3611643
Subject(s) - aerospace , bioengineering , communication, networking and broadcast technologies , components, circuits, devices and systems , computing and processing , engineered materials, dielectrics and plasmas , engineering profession , fields, waves and electromagnetics , general topics for engineers , geoscience , nuclear engineering , photonics and electrooptics , power, energy and industry applications , robotics and control systems , signal processing and analysis , transportation
This paper focuses on task allocation for multi-UAV collaborative power inspection at a single parking point, proposing an optimization method to minimize the total inspection time per parking. Key contributions include: 1) establishing a dynamic model for multi-rotor UAVs and a collaborative inspection model with clear assumptions; 2) developing a technical route covering task allocation, path planning, and conflict detection; 3) designing an immune algorithm-based parking point selection method and a UAV-operation vehicle collaborative inspection model; 4) implementing a genetic algorithm for sparse tower scenarios and a variable neighborhood search (VNS) algorithm for dense scenarios; 5) studying anti-collision path planning and optimizing takeoff/landing strategies. Case simulations verify the algorithms' effectiveness in different scenarios, providing a practical UAV allocation scheme to enhance inspection efficiency.

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