大型复杂海洋环境下AUV的长期自主任务规划

Dunwen Wei, Feiran Wang, Hongjiao Ma
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引用次数: 4

摘要

自主水下航行器(auv)已广泛用于执行海洋任务。长期自主任务规划是制约其在大规模复杂海洋环境中应用的难题。本文提出了一种考虑任务属性和海洋环境约束等多种复杂约束的任务规划模型。构建安全态势图,将任务规划转化为考虑时间成本、任务完成质量和数量的多目标优化问题。这样的模型具有可扩展性特性,您可以将自定义目标与额外的约束关联起来。考虑到该问题是一个NP最优问题,我们使用了元启发式算法-蚁群及其变体-来证明算法的正确性和有效性,并通过实验仿真比较了不同变体算法的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Long-term Autonomous Mission Planning of AUV in Large-scale Complex Marine Environment
Autonomous underwater vehicles (AUVs) have been widely used to perform marine missions. Long-term autonomous mission planning is the challenge issue that restricts their applications to the large-scale complex marine environment. In this paper, we proposed one mission planning model, which considers the various complex constraints, such as task attributes and marine environment constraints. We constructed the security situation map and formulated the mission planning into a multi-objective optimization problem that considers the time cost, the quality and quantity of completed tasks. Such a model has the extensibility features that you can associate your custom objective with extra constraints. Considering that this problem is an NP optimal problem, we used the metaheuristic algorithm -ant colony and its variants- to prove the correctness and effectiveness, and the performance of different variant algorithms are compared by the experimental simulations.
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