[4] [4] BAI X, JIANG H K, CUI J J, et al.UAV path planning based on improved A* and DWA algorithms［J］．International Journal of Aerospace Engineering, 2021, 2021:4511252．

[6] [6] PHUNG M D, HA Q P.Safety-enhanced UAV path planning with spherical vector-based particle swarm optimization［J］.Applied Soft Computing, 2021, 107:107376．

[7] [7] GE F W, LI K, HAN Y, et al.Path planning of UAV for oilfield inspections in a three-dimensional dynamic environment with moving obstacles based on an improved pigeon-inspired optimization algorithm［J］.Applied Intelligence, 2020, 50:2800-2817.

[8] [8] SONG P C, PAN J S, CHU S C.A parallel compact cuckoo search algorithm for three-dimensional path planning［J］.Applied Soft Computing, 2020, 94:106443.

[9] [9] ZERVOUDAKIS K, TSAFARAKIS S.A mayfly optimization algorithm［J］.Computers & Industrial Engineering, 2020, 145:106559.

[10] [10] WANG X, PAN J S, YANG Q, et al.Modified mayfly algorithm for UAV path planning［J］.Drones, 2022, 6(5):134.

[11] [11] DU Q H, ZHU H H.Dynamic elite strategy mayfly algorithm［J］.PLoS ONE, 2022, 17(8):e0273155.

[14] [14] YAN Z P, YAN J Y, WU Y F, et al.An improved hybrid mayfly algorithm for global optimization［J］.The Journal of Supercomputing, 2022, 79:5878-5919.

[17] [17] XUE Y B, ZHANG D D, LI L D, et al.Lightweight multi-scale convolutional neural network for real time stereo matching［J］.Image and Vision Computing, 2022, 124:104510.

[18] [18] MA Q M, JIANG G, WU J J, et al.WGLSM:an end-to-end line matching network based on graph convolution［J］.Neurocomputing, 2021, 453:195-208.

[19] [19] HU J Y, NIU H L, CARRASCO J, et al.Fault-tolerant cooperative navigation of networked UAV swarms for forest fire monitoring［J］.Aerospace Science and Technology, 2022, 123:107494.

[20] [20] MIAO Y M, HWANG K, WU D, et al.Drone swarm path planning for mobile edge computing in Industrial Internet of Things［J］.IEEE Transactions on Industrial Informatics, 2022, 19(5):6836-6848.