Underwater vehicles have been widely used in various ocean exploration missions due to their autonomous,flexible,safe,and reliable characteristics.However,their path planning still face problems such as poor performance and in-sufficient security.This article establishes an underwater vehicle path planning model with path safety as the constraint and minimizing the total length of the path as the objective function.In response to the solving requirements of the model,this article introduces the differential evolution operator into the grey wolf optimizer to improve its global exploration ability and calls the improved algorithm the differential grey wolf optimizer(DGWO).The simulation results show that the proposed DGWO can plan safe and economic paths for the underwater vehicle.Additionally,the DGWO not only has obvious advant-ages in planning solutions and convergence rates but also has broad engineering application value.
underwater vehicledifferential evolutiongrey wolf optimizerpath planningconstrained optimization
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