采样(信号处理)
天蓬
作物
农业
农业工程
行裁剪
高粱
环境科学
机器人
钥匙(锁)
农用地
计算机科学
农学
遥感
人工智能
探测器
工程类
地理
生物
生态学
电信
计算机安全
作者
Kitae Kim,Aarya Deb,David J. Cappelleri
出处
期刊:IEEE robotics and automation letters
日期:2022-07-01
卷期号:7 (3): 7942-7949
被引量:4
标识
DOI:10.1109/lra.2022.3187275
摘要
In this work, we present a novel agricultural robot called the Purdue AgBot or P-AgBot that has been designed for in-row and under canopy crop monitoring and physical sampling. We suggest approaches to autonomous navigation, crop monitoring, and crop sampling that can be applied in crop rows and under canopies for different agricultural environments. Each monitoring approach was designed to extract key morphological characteristics of the crops. The proposed approaches of P-AgBot have been experimentally verified not only in simulation but also with real corn and sorghum crops. Crop heights and stalk diameters are able to be estimated in real-time with less than 10% error. Vision-based detection of leaf samples was implemented and physical sampling is accomplished with a more than 80% success rate.
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