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To address the altitude-constrained path planning problem for Unmanned Underwater Vehicles (UUVs) in complex terrain environments, this paper proposes an improved hybrid A^* path planning algorithm based on UUV motion characteristics, termed UUVA^*. Firstly, the traditional hybrid A^* algorithm is extended by expanding the state space and incorporating the nonholonomic motion constraints of UUVs. Secondly, motion primitives tailored to UUV navigation characteristics are designed, and the cost function is optimized to generate smoother and more navigable paths. Finally, to enhance search efficiency, a multi-resolution hierarchical search strategy and branch pruning mechanism are introduced, significantly reducing the number of node expansions. Simulation tests conducted in two representative complex terrains—submarine hills, and submarine canyons—verify the altitude-constrained planning capability of the proposed algorithm. Furthermore, comparative experiments against classical A^* algorithm, hybrid A^*, and RRT^* algorithms are conducted. The result shows that the generated paths are smoother and yield smaller tracking errors, making the proposed algorithm more suitable for practical UUV applications, which verifies the superior performance of the proposed method in terms of trajectory tracking error and path navigability.

, authors=Zheping Yan^*, Yue Dong, authorsList=Zheping Yan, Yue Dong, authorCompany=null, correspAuthors=Zheping Yan, authorNote=null, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=null, pdfFileSize=null, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, fund=null), CN=ArticleExt(id=1311360868533760209, articleId=1311360867938169039, tenantId=1146029695717560320, journalId=1240618002186551303, language=CN, title=基于UUV模型的三维混合A^*定高路径规划, columnId=1240655021528904650, journalTitle=中国航海, columnName=智能航运, runingTitle=null, highlight=null, articleAbstract=

针对无人水下航行器（UUV）在复杂地形环境下的定高路径规划问题，提出了一种基于UUV运动特性改进的混合A^*路径规划算法（UUVA^*）。首先，结合UUV的非完整运动约束，对传统混合A^*算法进行状态空间扩展。其次，设计了适应UUV航行特性的运动基元，同时对代价函数进行优化，引导生成平滑且适航的路径。最后，为提高搜索效率，本文引入了多分辨率分层搜索与分支修剪机制，显著减少了节点扩展数量。通过在海底山丘、海底峡谷两种典型复杂地形下的仿真测试，验证了算法的定高规划能力，并与经典A^*、混合A^*算法和RRT^*算法进行对比仿真试验。结果表明，所提算法生成的路径更加平滑，UUV跟踪误差更小，更适合实际应用，验证了本文方法在轨迹跟踪误差和路径可航行性方面的优越性。

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