Route planning algorithm for autonomous underwater vehicles based on the hybrid of particle swarm optimization algorithm and radial basis function

The mission route plays an essential role for the mission security and reliability of an unmanned system. This paper gives a route planning method for autonomous underwater vehicles (AUVs) based on the hybrid of particle swarm optimization (PSO) algorithm and radial basis function (RBF). In the improved PSO algorithm, metropolis criterion is used to prevent the improved PSO algorithm from falling into local optimum and RBF is used to smooth the path planned by PSO algorithm. Compared with classic PSO algorithm, the hybrid algorithm of PSO and RBF can avoid falling into the local optimum effectively and plan an anti-collision route. Moreover, based on the simulation results, it can be seen that the approach presented here is more efficient in convergence performance, and the planned route requires lower performance of AUVs.