Increasing Efficiency of Grid Free Path Planning by Bounding the Search Region*

Seth Tau, S. Brennan, K. Reichard, J. Pentzer, D. Gorsich
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Abstract

Path planning for mobile robotics is a topic that has been studied for many decades, with many different formulations and goals. Considering obstacle avoidance with the very simple goal of minimizing the path distance from a start to end location, even this focused problem has attracted many solutions. The aspect of the problem studied in detail here is motivated by the question: what extent of the map needs to be considered by an algorithm to guarantee that the shortest path solution is within the considered extent? The algorithm presented in this paper examines this question in detail, revealing that the area of consideration can be calculated in stages of progress through a known map. Using this bound, the paper then proposes a method for guaranteeing the shortest path, while attempting to minimize the calculation time and memory requirements caused by consideration of map areas that would not admit the optimal path.
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利用边界搜索区域提高网格自由路径规划效率*
移动机器人的路径规划是一个已经研究了几十年的主题,有许多不同的公式和目标。考虑到以最小化从起点到终点的路径距离为简单目标的避障问题,即使是这个集中的问题也吸引了许多解决方案。这里详细研究的问题是由这样一个问题引起的:算法需要考虑映射的多大程度才能保证最短路径解在考虑的范围内?本文提出的算法详细研究了这个问题,揭示了可以通过已知地图在进度阶段计算考虑的区域。利用这一界限,提出了一种保证最短路径的方法,同时尽量减少由于考虑不允许最优路径的地图区域而导致的计算时间和内存需求。
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