系统分析用于密集果园定位的扫描匹配技术

IF 6.3 Q1 AGRICULTURAL ENGINEERING
Javier Guevara , Jordi Gené-Mola , Eduard Gregorio , Fernando A. Auat Cheein
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引用次数: 0

摘要

近年来,人们研究了不同的方法来确定机械在小树林中的位置,作为在全球导航卫星系统(GNSS)信号闭塞情况下补充 GNSS(全球导航卫星系统)信息的替代方法。当农业机械在茂密的树叶下或山坡上行驶时,就会出现这种情况。扫描匹配技术是对机械进行定位的一种可行解决方案,在必要时可补充全球导航卫星系统信号的缺失。然而,由于在异质、非结构化和非刚性环境(如果园植物)中难以获得关键点,扫描匹配技术在农业环境中的性能往往会下降。本文建议将点云划分为水平段和垂直段,以提高扫描匹配方法在果园中的性能。本文还研究了注册帧重叠的最佳方式。我们在富士苹果园进行了大量实验,验证了上述分析。结果表明,扫描匹配技术的累积定位误差可以通过选择果园的部分区域而明显减少,最多可减少 60%。本文所做的实验表明,所提出的方法可以在中长路径上对全球导航卫星系统导航进行补充。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A systematic analysis of scan matching techniques for localization in dense orchards
In recent years, different methods have been studied to determine machinery position within a grove, as an alternative for complementing GNSS (global navigation satellite system) information in cases where GNSS signal is occluded. Such a situation can be observed when agricultural machinery travels under dense foliage or on the slopes of mountains. Scan matching techniques arise as a possible solution for localizing the machinery, complementing the absence of the GNSS signal when necessary. However, since key points are difficult to obtain in heterogeneous, unstructured and non-rigid environments (such as orchard plants), the performance of scan matching techniques often decreases in agricultural environments. This paper suggests dividing the point clouds into horizontal and vertical segments to improve the performance of scan-matching methods in orchards. It also examines the best way for registered frames to overlap. We validate the analysis with extensive experimentation in a Fuji apple orchard. The results show that the cumulative localization error in scan matching techniques can be notoriously decreased with selective parts of the orchard, by up to 60%. The experimentation performed herein suggests that the proposed methodology can complement the GNSS navigation in a middle-long path.
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CiteScore
4.20
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