摘要
阐述智慧农业中的植保无人机技术应用。探讨农业植保无人机喷洒农药的可行性,提出一种基于深度学习的方法,利用捷联式惯性导航系统、卡尔曼滤波算法和PID等算法保证植保无人机的性能稳定,利用卷积神经网络(CNN)、聚类分析和认知计算处理图像和数据。
This paper expounds the application of crop protection unmanned aerial vehicle technology in smart agriculture.It explores the feasibility of pesticide spraying by agricultural crop protection drones and proposes a deep learning based method that utilizes strapdown inertial navigation systems,Kalman filtering algorithms,and PID algorithms to ensure the stable performance of crop protection drones.Convolutional neural networks(CNN),clustering analysis,and cognitive computing are used to process images and data.
作者
王晴
王柄昆
李婧
刘伟
齐秋红
WANG Qing;WANG Bingkun;LI Jing;LIU Wei;QI Qiuhong(School of Information and Control Engineering,Shenyang Urban Construction College,Liaoning 110167,China)
出处
《集成电路应用》
2024年第8期75-77,共3页
Application of IC
基金
2023年大学生创新创业训练计划项目(202313208024)。
关键词
捷联式惯性导航系统
卡尔曼滤波算法
PID算法
卷积神经网络
聚类分析
认知计算
strapdown inertial navigation system
Kalman filter algorithm
PID algorithm
Convolutional Neural Network
cluster analysis
cognitive computing
