Tree centric localisation in almond orchards
Tree centric localisation in almond orchards
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杏仁园以树木为中心的定位
DOI：
10.17660/actahortic.2016.1130.92
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发表时间：
2016
期刊：
影响因子：
--
通讯作者：
S. Sukkarieh
中科院分区：
文献类型：
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作者：
J. Underwood;Gustav Jagbrant;Juan I. Nieto;S. Sukkarieh
机器人和智能传感系统可以提供有用的信息，以提高特种作物生产的产量和质量。treecrop应用程序的一个关键要求是能够将传感数据与果园中的单个树木相关联。一个移动的地面机器人与扫描激光雷达（激光测距传感器）被用来建立一个三维（3D）模型的果园和算法推导出自动检测和分割每棵树。每个树冠的高度轮廓用于将树与先前获得的数据库相匹配，以确定机器人在果园中的位置，并将新获得的农艺数据与现有数据库相关联。在维多利亚米尔杜拉的杏仁果园的2.3公顷区域中进行了16个月的实验。一个平均的树分割精度为99.1%，和定位精度为98.2%的数据获得一个完整的一年。该方法是足够准确的本地化和果园环境中的数据管理提供了一个可行的机制。
Robotics and intelligent sensing systems can provide useful information to improve yield and quality in specialty crop production. A key requirement for treecrop applications is the ability to associate sensed data to the individual trees in an orchard. A mobile ground robot with a scanning lidar (laser range sensor) is used to build a three dimensional (3D) model of an orchard and algorithms are derived to automatically detect and segment each tree. The height profile of each canopy is used to match the tree to a previously obtained database, to determine the location of the robot in the orchard, and to associate newly obtained agronomic data to the existing database. Experiments were conducted over 16 months in a 2.3 ha section of an almond orchard in Mildura, Victoria. An average tree segmentation accuracy of 99.1% was obtained, and the localisation accuracy was 98.2% for data obtained one full year apart. The method is sufficiently accurate to provide a feasible mechanism for localisation and data management in orchard environments.