Xu Rui, Li Changying
Bio-Sensing and Instrumentation Laboratory, College of Engineering, The University of Georgia, Athens, USA.
Phenomics and Plant Robotics Center, The University of Georgia, Athens, USA.
Plant Phenomics. 2022 Jun 16;2022:9760269. doi: 10.34133/2022/9760269. eCollection 2022.
Manual assessments of plant phenotypes in the field can be labor-intensive and inefficient. The high-throughput field phenotyping systems and in particular robotic systems play an important role to automate data collection and to measure novel and fine-scale phenotypic traits that were previously unattainable by humans. The main goal of this paper is to review the state-of-the-art of high-throughput field phenotyping systems with a focus on autonomous ground robotic systems. This paper first provides a brief review of nonautonomous ground phenotyping systems including tractors, manually pushed or motorized carts, gantries, and cable-driven systems. Then, a detailed review of autonomous ground phenotyping robots is provided with regard to the robot's main components, including mobile platforms, sensors, manipulators, computing units, and software. It also reviews the navigation algorithms and simulation tools developed for phenotyping robots and the applications of phenotyping robots in measuring plant phenotypic traits and collecting phenotyping datasets. At the end of the review, this paper discusses current major challenges and future research directions.
在田间对植物表型进行人工评估可能会耗费大量人力且效率低下。高通量田间表型分析系统,尤其是机器人系统,在实现数据收集自动化以及测量以前人类无法获取的新型和精细尺度表型性状方面发挥着重要作用。本文的主要目标是回顾高通量田间表型分析系统的最新进展,重点关注自主地面机器人系统。本文首先简要回顾了非自主地面表型分析系统,包括拖拉机、手动或电动推车、龙门架和电缆驱动系统。然后,针对自主地面表型分析机器人的主要组件,包括移动平台、传感器、操纵器、计算单元和软件,进行了详细回顾。还回顾了为表型分析机器人开发的导航算法和仿真工具,以及表型分析机器人在测量植物表型性状和收集表型数据集方面的应用。在综述结尾,本文讨论了当前的主要挑战和未来的研究方向。