The bacterial foraging optimisation (BFO) algorithm is a commonly adopted bio-inspired optimisation algorithm. However, BFO is not a proper choice in coping with continuous global path planning in the context of unmanned surface vehicles (USVs). In this paper, a grid partition-based BFO algorithm, named AS-BFO, is proposed to address this issue in which the enhancement is contributed by the involvement of the A* algorithm. The chemotaxis operation is redesigned in AS-BFO. Through repeated simulations, the relative optimal parameter combination of the proposed algorithm is obtained and the most influential parameters are identified by sensitivity analysis. The performance of AS-BFO is evaluated via five size grid maps and the results show that AS-BFO has advantages in USV global path planning.

中文翻译：

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一种基于A*的无人水面航行器全局路径规划细菌觅食优化算法

细菌觅食优化（BFO）算法是一种常用的仿生优化算法。然而，在无人水面航行器（USV）的背景下，BFO 并不是应对连续全局路径规划的正确选择。在本文中，提出了一种基于网格划分的 BFO 算法，称为 AS-BFO，以解决此问题，其中 A* 算法的参与有助于增强。在 AS-BFO 中重新设计了趋化性操作。通过反复仿真，得到所提算法的相对最优参数组合，并通过敏感性分析识别出影响最大的参数。通过五种尺寸的网格图对AS-BFO的性能进行评估，结果表明AS-BFO在USV全局路径规划中具有优势。