摘要
建立了采摘机器人运动学模型,并设计了基于深度神经网络和大数据技术的多元信息融合模型,实现了对采摘机器人的定位和轨迹预测。仿真结果表明:模型对采摘机器人的预测精度较高,误差在允许的范围内,对采摘机器人定位和轨迹预测具有一定参考意义。
It first establishes the kinematics model of the picking robot,and then designs a multi information fusion model based on deep neural network and big data technology to achieve the positioning and trajectory prediction of the picking robot.The simulation results show that the prediction accuracy of the model for the picking robot is high,and the error is within the allowable range,which proves that the model has certain reference significance for the location and trajectory prediction of the picking robot.
作者
聂恒志
吴升
张璐
Nie Hengzhi;Wu Sheng;Zhang Lu(Academy of Digital China(Fujian),Fuzhou University,Fuzhou 350003,China;Henan Polytechnic Institute,Nanyang 473000,China)
出处
《农机化研究》
北大核心
2024年第4期53-57,共5页
Journal of Agricultural Mechanization Research
基金
河南省教育规划项目(2020YB0527)。
关键词
采摘机器人
定位
轨迹预测
大数据
神经网络
信息融合
picking robot
location
track prediction
big data
neural network
information fusion
