[2] [2] CAO H H,ZHANG H P,LIU Z D,et al.UAV path planning based on improved particle swarm algorithm［C］//The 7th International Symposium on Mechatronics and Industrial Informatics(ISMII).Zhuhai:IEEE,2021:284-287.

[3] [3] ALRASLAN M,ALKURDI A H.UAV path planning using genetic algorithm with parallel implementation［J］.International Journal of Computational Science and Information Technology,2022,10(2):1-15.

[5] [5] SUN Y H,CHEN W Q,LYU J Y.UAV path planning based on improved artificial potential field method［C］//International Conference on Computer Network Electronic and Automation (ICCNEA).Xian:IEEE,2022:95-100.

[8] [8] DORIGO M,MANIEZZO V,COLORNI A.Ant system:optimization by a colony of cooperating agents［J］.IEEE Transactions on SystemsManand CyberneticsPart B,1996,26(1):29-41.

[12] [12] CHEN X Y,DAI Y H.Research on an improved ant colony algorithm fusion with genetic algorithm for route planning［C］//IEEE 4th Information TechnologyNetworkingElectronic and Automation Control Conference (ITNEC).Chongqing:IEEE,2020:1273-1278.

[13] [13] ZHANG W H,ZHANG P.Improvement of UAV track trajectory algorithm based on ant colony algorithm［C］//International Conference on Intelligent TransportationBig Data & Smart City (ICITBS).Changsha: IEEE,2019:28-31.

[17] [17] CHEN Y,WU J F,HE C S,et al.Intelligent ware house robot path planning based on improved ant colony algorithm［J］.IEEE Access,2023,11(3):12360-12367.