果园设置中的视觉伺服

Nicolai Häni, Volkan Isler
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引用次数: 2

摘要

我们提出了一个通用框架,用于精确定位传感器和末端执行器在农场设置使用安装在机器人操纵器上的相机。我们的主要贡献是一种基于新的鲁棒特征跟踪算法的视觉伺服方法。在苹果园进行的现场实验结果表明,即使在强风、光照条件变化和目标物体部分遮挡等环境影响下,我们的方法也收敛于给定的终止标准。此外,我们通过实验证明,该系统收敛到期望的视图在很大范围内的初始条件。这种方法为自动水果检测、水果采摘或精确农药施用等新应用开辟了可能性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Visual servoing in orchard settings
We present a general framework for accurate positioning of sensors and end effectors in farm settings using a camera mounted on a robotic manipulator. Our main contribution is a visual servoing approach based on a new and robust feature tracking algorithm. Results from field experiments performed at an apple orchard demonstrate that our approach converges to a given termination criterion even under environmental influences such as strong winds, varying illumination conditions and partial occlusion of the target object. Further, we show experimentally that the system converges to the desired view for a wide range of initial conditions. This approach opens possibilities for new applications such as automated fruit inspection, fruit picking or precise pesticide application.
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