AUV 3D global path planning based on IACO-GA-IPSO fusion algorithm
To overcome challenges faced by conventional ant colony and particle swarm optimization algorithms,an IACO-GA-IPSO path planning algorithm is proposed,which integrates the improved ant colony algorithm(IACO),im-proved particle swarm algorithm(IPSO),and genetic algorithm(GA).Firstly,a 3D marine environment model is defined,with the workspace divided into horizontal grid planes along the Z-axis.Secondly,A multi-standard path evaluation model is established.Finally,the fusion algorithm generates paths:the IACO algorithm generates a suboptimal population,the GA al-gorithm optimizes population diversity,and the IPSO algorithm quickly converges to the global optimum.The experimental results show that the fusion algorithm can fully leverage the advantages of each algorithm,overcome the contradiction between population size and convergence speed,optimize the initial population,improve global search ability,local search accuracy,and algorithm operation efficiency,accelerate convergence speed,and avoid falling into local optimal paths.
AUV 3D path planningfusion intelligent algorithmimproved ant colony algorithmimproved particle swarm algorithmgenetic algorithm
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