Robot exploration with fast frontier detection: theory and experiments
Robot exploration with fast frontier detection: theory and experiments
复制标题
具有快速前沿检测的机器人探索：理论与实验
DOI：
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发表时间：
2012
期刊：
影响因子：
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通讯作者：
G. Kaminka
中科院分区：
文献类型：
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作者：
Matan Keidar;G. Kaminka
基于前沿的探索是最常见的探索方法，这是机器人学中的一个基本问题。在基于边界的探索中，机器人通过重复计算(并向)边界移动来进行探索，边界是将已知区域与未知区域分开的部分。然而，大多数边界检测算法处理的是整个地图数据。这可能是一个耗时的过程，会减慢探索的速度。本文提出了两种新的边缘检测算法：基于图搜索的WFD算法和只处理新的激光读数数据的FFD算法。与最先进的方法相比，这两种算法都不处理整个地图数据。我们实现了这两种算法，并表明这两种算法都比最先进的边界探测器实现(快几个数量级)。
Frontier-based exploration is the most common approach to exploration, a fundamental problem in robotics. In frontier-based exploration, robots explore by repeatedly computing (and moving towards) frontiers, the segments which separate the known regions from those unknown. However, most frontier detection algorithms process the entire map data. This can be a time consuming process which slows down the exploration. In this paper, we present two novel frontier detection algorithms: WFD, a graph search based algorithm and FFD, which is based on processing only the new laser readings data. In contrast to state-of-the-art methods, both algorithms do not process the entire map data. We implemented both algorithms and showed that both are faster than a state-of-the-art frontier detector implementation (by several orders of magnitude).