Task Allocation Optimization for Multi-UAV Collaborative Power Inspection at Single Parking Point
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.
Authors
- Zhike Wen
- Han Cai
- Zhuang Liu
- Ning Yang (ORCID: https://orcid.org/0009-0001-5231-9967)
- Guiwei Shao
- Liwei Zhou (ORCID: https://orcid.org/0000-0003-1692-9263)
Institutions
- China Power Engineering Consulting Group (China) (CN)
- China National Electric Apparatus Research Institute (China) (CN)
Publication Details
- Journal
- IEEE Access
- Published
- 2025-01-01
- DOI
- https://doi.org/10.1109/access.2025.3611643
- Primary Topic
- Smart Parking Systems Research
- Type
- article
- Field-Weighted Citation Impact
- 0.00