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An obstacle-avoidance technique for autonomous underwater vehicles based on BK-products of fuzzy relation

机译:基于模糊关系BK乘积的自动驾驶水下航行器避障技术

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This paper proposes a new heuristic search technique for obstacle avoidance of autonomous underwater vehicles (AUVs) that are equipped with a looking-ahead obstacle-avoidance sonar. The fuzzy relation between the sonar sections and the properties of a real-time environment is used as a core concept. The Lukasiewicz fuzzy implication operator is used in Bandler and Kohout's Triangle Subproduct to calculate the relationship between the fuzzy relation and its transposed relation. This product relation the reveals the characteristics and interrelationships of the sonar sections. A direction of the sonar section that has good characteristics is selected as the successive heading for obstacle avoidance of AUVs. The simulation results clearly demonstrate that the heuristic search technique, which uses the BK-product of a fuzzy relation with a sonar partitioned into seven sections, enables AUVs to navigate safely through the obstacle to the goal with the optimal path.
机译:本文提出了一种新的启发式搜索技术,用于装备有超前避障声纳的自动水下航行器(AUV)的避障。声纳截面与实时环境属性之间的模糊关系被用作核心概念。在Bandler和Kohout的Triangle Subproduct中使用Lukasiewicz模糊蕴涵算子来计算模糊关系及其转置关系之间的关系。这种产品关系揭示了声纳截面的特征和相互关系。选择具有良好特性的声纳截面的方向作为AUV避障的连续航向。仿真结果清楚地表明,启发式搜索技术将模糊关系的BK乘积与声纳划分为七个部分,从而使AUV能够以最佳路径安全地越过目标障碍物。

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