This paper proposes an algorithm that combines global and local dynamic path-planning methods to solve the dynamic path-planning problem for unmanned underwater vehicles(UUVs)in near-shore environments.First,a fast-ex-panding random tree algorithm based on adaptive target guidance is proposed to increase the directionality of random tree growth.The algorithm then achieves rapid convergence using turning and reselection strategies to reduce ineffect-ive expansion.Further,an adaptive sub-node selection strategy is used after obtaining the global path to acquire sub-tar-get points for the dynamic window approach.This approach decomposes the complex global dynamic task planning in-to multiple simple dynamic path-planning tasks,preventing the dynamic window approach from falling into local min-ima.Finally,the effectiveness and practicality of the algorithm are verified using simulation experiments of UUV depar-ture tasks.
维普
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