A Hybrid Routing Approach Using Two Searching Layers

IF 0.5 Q4 ENGINEERING, ELECTRICAL & ELECTRONIC
G. Koca, Seda Yetkin
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引用次数: 0

Abstract

Abstract This paper considers SUB_GOALs by using basic A* algorithm and Subgoal Graphs in a hybrid approach to execute optimal route. SUB_GOALs identified with pre-searching from basic A* at break points and Subgoal Graphs at corners of obstacles are added to SUB_TABLE to expedite the final searching in the hybrid approach. Map to work on is divided to subregions with decision-making process by using line-of-sight to avoid redundant searching. In the final searching layer, all feasible SUB_GOALs gained from decision-making process in the same subregion are connected to find final solutions of routes. Solutions achieved in the divided subregions are evaluated and combined to discover the final optimal route. The proposed hybrid approach is applied to three different scenarios in various dimensions of maps. In these three scenarios, the shortest route without hitting obstacles is calculated as 46.67, 57.76 and 124.7 units, respectively, and compared with other search algorithms. Simulation results of route planning are demonstrated to exhibit the effectiveness of the proposed hybrid approach.
一种使用两个搜索层的混合路由方法
摘要本文通过使用基本A*算法和子目标图的混合方法来考虑SUB_GOALs,以执行最优路由。通过在断点处从基本A*进行预搜索而识别的SUB_GOAL和在障碍物拐角处的子目标图被添加到SUB_TABLE中,以加快混合方法中的最终搜索。通过使用视线进行决策过程,将要绘制的地图划分为多个子区域,以避免重复搜索。在最终搜索层,将同一子区域决策过程中获得的所有可行的SUB_GOAL连接起来,以找到路线的最终解。对在划分的子区域中实现的解决方案进行评估和组合,以发现最终的最佳路线。所提出的混合方法应用于不同维度地图中的三种不同场景。在这三种情况下,无障碍物的最短路径分别计算为46.67、57.76和124.7个单位,并与其他搜索算法进行了比较。仿真结果表明了该混合方法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Electrical Control and Communication Engineering
Electrical Control and Communication Engineering ENGINEERING, ELECTRICAL & ELECTRONIC-
自引率
14.30%
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0
审稿时长
12 weeks
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