植物图片包含植物生境、物种组成、形态特征、物候等相关信息,是野外调查和植物记录的重要资料。无人机可按照设定程序定时、定航线拍摄植物,获取植物图片拍摄地的精准位置信息,进而实现周期化的植物拍摄和调查。本图片数据集系于2022–...植物图片包含植物生境、物种组成、形态特征、物候等相关信息,是野外调查和植物记录的重要资料。无人机可按照设定程序定时、定航线拍摄植物,获取植物图片拍摄地的精准位置信息,进而实现周期化的植物拍摄和调查。本图片数据集系于2022–2023年在内蒙古呼伦贝尔湿润草原、锡林浩特典型草原、鄂尔多斯干旱草原选地,依照《草地植物多样性无人机调查技术规范》(T/CSES 123-2023)团体标准,以DJI MINI 3 PRO无人机采集而来,并以人工框选和鉴定为主、目标检测和智能识别模型处理为辅的方式进行了图像中的植物框选和鉴定。本数据集包含了19科32属40种植物的4000幅图片、植物物种名称、植物科属信息、采集时间、采集点海拔、经纬度。本数据集可以为相关草地植物的形态、分布、物候等信息检索以及智能识别模型构建提供数据支撑。展开更多
The current literature lacks uniform calculation methods for following trajectory control for autonomous vehicles,including the calculation of errors,determination of tracking points,and design of feedforward controll...The current literature lacks uniform calculation methods for following trajectory control for autonomous vehicles,including the calculation of errors,determination of tracking points,and design of feedforward controllers.Hence,a complete calculation method is proposed to address this gap.First,a control equation in the form of an error is obtained according to the dynamic equation of the vehicle coordinate system and the trajectory following model.Secondly,the deviation of the vehicle state is obtained according to the current vehicle s state and the following control model.Finally,a linear quadratic regulator(LQR)controller with feedforward control is designed according to the characteristics of the dynamic equation.With the proposed LQR,the simulation of computational time,anti-interference,and reliability analysis of the trajectory following control is performed by programming using MATLAB.The simulation outcomes are then compared with the experimental results from the literature.The comparison indicates that the proposed complete calculation method is effective,reliable,and capable of achieving real-time and anti-interference following control performance.The simulation results with or without feedforward control show that the steady-state error is eliminated and that good control performance is obtained by introducing feedforward control.展开更多
文摘植物图片包含植物生境、物种组成、形态特征、物候等相关信息,是野外调查和植物记录的重要资料。无人机可按照设定程序定时、定航线拍摄植物,获取植物图片拍摄地的精准位置信息,进而实现周期化的植物拍摄和调查。本图片数据集系于2022–2023年在内蒙古呼伦贝尔湿润草原、锡林浩特典型草原、鄂尔多斯干旱草原选地,依照《草地植物多样性无人机调查技术规范》(T/CSES 123-2023)团体标准,以DJI MINI 3 PRO无人机采集而来,并以人工框选和鉴定为主、目标检测和智能识别模型处理为辅的方式进行了图像中的植物框选和鉴定。本数据集包含了19科32属40种植物的4000幅图片、植物物种名称、植物科属信息、采集时间、采集点海拔、经纬度。本数据集可以为相关草地植物的形态、分布、物候等信息检索以及智能识别模型构建提供数据支撑。
基金The National Key Research and Development Program of China(No.2019YFB2006404)Guangxi Science and Technology Major Project(No.GUIKE AA18242036,No.GUIKE AA18242037).
文摘The current literature lacks uniform calculation methods for following trajectory control for autonomous vehicles,including the calculation of errors,determination of tracking points,and design of feedforward controllers.Hence,a complete calculation method is proposed to address this gap.First,a control equation in the form of an error is obtained according to the dynamic equation of the vehicle coordinate system and the trajectory following model.Secondly,the deviation of the vehicle state is obtained according to the current vehicle s state and the following control model.Finally,a linear quadratic regulator(LQR)controller with feedforward control is designed according to the characteristics of the dynamic equation.With the proposed LQR,the simulation of computational time,anti-interference,and reliability analysis of the trajectory following control is performed by programming using MATLAB.The simulation outcomes are then compared with the experimental results from the literature.The comparison indicates that the proposed complete calculation method is effective,reliable,and capable of achieving real-time and anti-interference following control performance.The simulation results with or without feedforward control show that the steady-state error is eliminated and that good control performance is obtained by introducing feedforward control.
