无人地面车辆
高光谱成像
多光谱图像
精准农业
人工智能
限制
RGB颜色模型
基本事实
地理参考
计算机视觉
农业
无人机
全球定位系统
机器人学
遥感
环境科学
计算机科学
工程类
地理
机器人
自然地理学
生物
机械工程
考古
遗传学
作者
Subodh Bhandari,Amar Raheja,Robert L. Green,Dat Do
摘要
This paper presents the work being conducted at Cal Poly Pomona on the collaboration between unmanned aerial and ground vehicles for precision agriculture. The unmanned aerial vehicles (UAVs), equipped with multispectral/hyperspectral cameras and RGB cameras, take images of the crops while flying autonomously. The images are post processed or can be processed onboard. The processed images are used in the detection of unhealthy plants. Aerial data can be used by the UAVs and unmanned ground vehicles (UGVs) for various purposes including care of crops, harvest estimation, etc. The images can also be useful for optimized harvesting by isolating low yielding plants. These vehicles can be operated autonomously with limited or no human intervention, thereby reducing cost and limiting human exposure to agricultural chemicals. The paper discuss the autonomous UAV and UGV platforms used for the research, sensor integration, and experimental testing. Methods for ground truthing the results obtained from the UAVs will be used. The paper will also discuss equipping the UGV with a robotic arm for removing the unhealthy plants and/or weeds.
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