To obtain the navigation path of high-performance unmanned surface vehicle(USV),a multi-strategy improved sparrow search algorithm(MISSA)was proposed.Firstly,a fitness function with a steering angle penalty term was de-signed.Secondly,the position update strategy was improved by using the golden sine method and parameter self-spiral set-ting,at the same time,information exchange between sparrow individuals was strengthened during the position update process to balance global exploration and local search proces-ses,again,chaotic circular mapping was introduced to im-prove the quality and diversity of the initial sparrow popula-tion.Finally,a local search optimization mechanism was de-signed to solve the problem of the original sparrow algorithm(SSA)easily falling into local optima and obtain a global path with better fitness.Results show that compared with three ex-cellent algorithms,namely improved A*,improved ant colony algorithm combined with genetics,and original SSA,the MIS-SA algorithm in this paper performs the best in key perform-ance indicators such as path distance,turning angle,and fre-quency,providing an effective path for autonomous and safe operation of USV.
维普
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