Can you pick a broccoli? 3D-vision based detection and localisation of broccoli heads in the field

Keerthy Kusumam, T. Krajník, S. Pearson, Grzegorz Cielniak, T. Duckett
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引用次数: 19

Abstract

This paper presents a 3D vision system for robotic harvesting of broccoli using low-cost RGB-D sensors. The presented method addresses the tasks of detecting mature broccoli heads in the field and providing their 3D locations relative to the vehicle. The paper evaluates different 3D features, machine learning and temporal filtering methods for detection of broccoli heads. Our experiments show that a combination of Viewpoint Feature Histograms, Support Vector Machine classifier and a temporal filter to track the detected heads results in a system that detects broccoli heads with 95.2% precision. We also show that the temporal filtering can be used to generate a 3D map of the broccoli head positions in the field.
你能摘花椰菜吗?基于3d视觉的西兰花头检测和定位
本文介绍了一种采用低成本RGB-D传感器的西兰花机器人收割3D视觉系统。所提出的方法解决了在田间检测成熟西兰花头并提供其相对于车辆的3D位置的任务。本文评估了用于检测西兰花头部的不同3D特征、机器学习和时间过滤方法。我们的实验表明,结合视点特征直方图、支持向量机分类器和时间滤波器来跟踪检测到的头部,系统检测西兰花头部的准确率达到95.2%。我们还表明,时间滤波可以用来生成西兰花在田间头部位置的3D地图。
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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