多智能体编队中人工势场法的改进研究

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DOI：10.16652/j.issn.1004-373x.2025.17.027 引用格式：，.多智能体编队中人工势场法的改进研究[J].现代电子技术，2025，48（17）：181-186.

关键词：人工势场法；多智能体编队；局部最小值；衰减权重；斥力计算；权重分配中图分类号：TN911.1-34；TP391.9 文献标识码：A 文章编号：1004-373X（2025）17-0181-06

Application of improved artificial potential field method in multi-agent formation control

HEXing¹，BAI Yanhong1，²

（1.SchoolofElectronicInformationEngineering，TaiuanUiversityofSienceandTechnology，TauanO3O24，Cina; ！CollegeoftellgentacuinustryaniUesityflctroicicdholoyinfea

Abstract：Sincethetraditionalartificialpotentialfieldmethodispronetofalingintolocalminima，animprovedartificial potentialfieldalgorithmwhichintroducesrepulsionattenuationweightisproposedaccording totheideaofdestroyingthe equilibriumstateofagentsatnon-targets.Thisalgorithmasignsweightstoobstaclesencounteredwithintheagent'sdetection rangeandapliestheseweightstothecalculationofrepulsiveforces exertedbytheobstacles.Theweightsdecayastheagent moves，ensuring thatthenetforceactingontheagentdoesnotbalanceoutbeforereaching thetarget，therebyalowing the agenttoescapelocalminia.Theresultsofthesimulationexperimentsdemonstratethat，incomparisonwiththetraditioalartificialpotentialfeldmethodandother methodsavoidinglocal minimasuchastherandomdisturbancemethodandtheedge-followingmethod，theproposedalgorithmavoidsthelocalminimaefectivelyandshowssignificantimprovementsinconvergence speed，stability and energy consumption.

Keywords：arificialpotentialfieldmethod;multi-agentformation;local minima;atenuationweight;repulsiveforcecalculation;weight allocation

0 引言

多智能体编队在军事、救援救灾、农业生产、仓储物流、交通管理等领域得到了广泛应用。（剩余6919字）