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.

翻译：我们向PATHobot展示了一个针对玻璃屋环境的自主作物测量和干预机器人。这个平台的目的是自主地收集高质量数据,并估算关键元素参数。为了实现这个目标,我们改造了一台现成的管道式管道式电车,配有一系列多式照相机、导航传感器和机器人臂,用于密切勘测任务和干预。在本文中,我们描述了PATHobot设计的选择,以确保在商业玻璃屋环境中进行适当操作。作为一个勘测平台,我们收集了许多数据集,其中包括甜辣椒和番茄。我们展示了PATHoBot是如何促成新式监测方法的,首先通过纳入轮式观察和深度信息改进我们以前关于水果计数的工作。我们发现,通过引入再投影和深度信息,我们能够在“野生”情况下对基线技术实现20点的绝对改进。最后,我们介绍了一个3D绘图案例研究,进一步展示了PATHoBot的作物测量能力。