论文标题
病原体：用于温室作物表型和干预的机器人
PATHoBot: A Robot for Glasshouse Crop Phenotyping and Intervention
论文作者
论文摘要
我们为玻璃屋环境提出了病原体的一项自动作物调查和干预机器人。该平台的目的是自主收集高质量数据，并估计关键的表型参数。为了实现这一目标，我们恢复了一个现成的管道轨道手推车，该手推车带有一系列多模式相机，导航传感器和机器人臂，用于密切的测量任务和干预。在本文中，我们描述了为确保在商业温室环境中进行适当操作而做出的病理设计选择。作为一个测量平台，我们收集了许多数据集，其中包括甜椒和西红柿。我们首先通过结合了轮子探光度和深度信息来展示病理科的如何通过改进我们先前的水果计数工作来实现新颖的监视方法。我们发现，通过引入重新投入和深度信息，我们可以在“野外”情况下的基线技术中获得20分的绝对改善。最后，我们提出了一个3D映射案例研究，进一步展示了Pathobot的作物测量能力。
We present PATHoBot an autonomous crop surveying and intervention robot for glasshouse environments. The aim of this platform is to autonomously gather high quality data and also estimate key phenotypic parameters. To achieve this we retro-fit an off-the-shelf pipe-rail trolley with an array of multi-modal cameras, navigation sensors and a robotic arm for close surveying tasks and intervention. In this paper we describe PATHoBot design choices made to ensure proper operation in a commercial glasshouse environment. As a surveying platform we collect a number of datasets which include both sweet pepper and tomatoes. We show how PATHoBot enables novel surveillance approaches by first improving our previous work on fruit counting by incorporating wheel odometry and depth information. We find that by introducing re-projection and depth information we are able to achieve an absolute improvement of 20 points over the baseline technique in an "in the wild" situation. Finally, we present a 3D mapping case study, further showcasing PATHoBot's crop surveying capabilities.
