Article: Multi-UAV path planning methodology for dual-task power inspection scenarios based on genetic algorithm Journal: International Journal of Systems, Control and Communications (IJSCC) 2026 Vol.17 No.9 pp.1 - 27 Abstract: With the continuous expansion of power systems, employing unmanned aerial vehicles (UAVs) for power inspection has become a practical necessity. In this paper, two critical inspection tasks in single-depot, multi-UAV scenarios are investigated: target point inspection and transmission line inspection. For the target point inspection problem, a mathematical model incorporating maximum flight distance constraints is established, and an improved genetic algorithm that integrates the 2-opt operator and an adaptive mutation rate mechanism is proposed. Experimental results demonstrate that the improved algorithm achieves superior solution quality and convergence stability. For the transmission line inspection problem, an optimisation model is developed to minimise the total flight distance. An adaptive genetic algorithm (AGA) is proposed to solve this model. Comparative experiments on maps of different scales verify that AGA significantly reduces the total flight distance and optimises the number of dispatched UAVs compared to the classical adaptive genetic algorithm. Inderscience Publishers - linking academia, business and industry through research

Title: Multi-UAV path planning methodology for dual-task power inspection scenarios based on genetic algorithm

Authors: Haitao Li; Chao Che; Chenyang Duan; Xin Zhang; Li Sun

Addresses: State Grid Changzhou Power Supply Company, Changzhou 213200, China ' State Grid Changzhou Power Supply Company, Changzhou 213200, China ' State Grid Changzhou Power Supply Company, Changzhou 213200, China ' State Grid Changzhou Power Supply Company, Changzhou 213200, China ' National Engineering Research Centre of Power Generation Control and Safety, Liyang Research Institute, Southeast University, Liyang 213300, China

Abstract: With the continuous expansion of power systems, employing unmanned aerial vehicles (UAVs) for power inspection has become a practical necessity. In this paper, two critical inspection tasks in single-depot, multi-UAV scenarios are investigated: target point inspection and transmission line inspection. For the target point inspection problem, a mathematical model incorporating maximum flight distance constraints is established, and an improved genetic algorithm that integrates the 2-opt operator and an adaptive mutation rate mechanism is proposed. Experimental results demonstrate that the improved algorithm achieves superior solution quality and convergence stability. For the transmission line inspection problem, an optimisation model is developed to minimise the total flight distance. An adaptive genetic algorithm (AGA) is proposed to solve this model. Comparative experiments on maps of different scales verify that AGA significantly reduces the total flight distance and optimises the number of dispatched UAVs compared to the classical adaptive genetic algorithm.

Keywords: unmanned aerial vehicles; UAVs; target point inspection; transmission line inspection; genetic algorithm; GA.

DOI: 10.1504/IJSCC.2026.156574

International Journal of Systems, Control and Communications, 2026 Vol.17 No.9, pp.1 - 27

Received: 07 Aug 2025
Accepted: 26 Jan 2026
Published online: 29 Sep 2026 *

Title: Multi-UAV path planning methodology for dual-task power inspection scenarios based on genetic algorithm

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