GNSS Field Unmanned Sprayer Control Technology And System Development

At present,with the continuous development of agricultural machinery and equipment intelligence and information technology,the application scenarios of speed control technology and extraction method in unmanned plant protection operation are more and more extensive.In this paper,the advantages and error analysis of single point speed measurement and visual speed measurement control methods in different environments are analyzed in detail.Based on Kalman filter algorithm,the two kinds of speed measurement data are fused to improve the situation that the speed measurement accuracy of agricultural vehicles is not enough in the field complex environment,which provides a strong support for the research of GNSS field unmanned pesticide vehicle control technology.The main work and conclusions are as follow:(1)Design and implementation of single point GNSS speed measurement control system.This topic takes the electric unmanned vehicle as the research object,through analyzing the GNSS signal fixed on the center line of the vehicle body,collecting the speed change of the unmanned vehicle in the process of driving.Through UART serial port,the data information is sent to STM32F103VET6 chip in real time,and the speed information is extracted by CPU.(2)Design and implementation of binocular vision speed measurement control system.Based on the principle of visual mileage,C + + code is run in Linux system to track the pixels in two adjacent images,find out the corresponding points of the pixels in the two images,and substitute the three-dimensional point coordinates of each group of corresponding points in the two images into the motion estimation equation to obtain the forward speed data of the spraying vehicle in real time.The experimental results show that the binocular speed measurement control system is generally stable at 0.1712m/s,and the variance is 0.0786,which improves the stability of the speed measurement control system.(3)The realization of the fusion algorithm and the integrated control of the system.Based on the Kalman filter algorithm,this project integrates the data of GNSS single point speed measurement and binocular vision speed measurement system,and outputs the fused data as the optimal value,which effectively makes up for the defect of GNSS drift phenomenon in the field low-speed operation mode,and completes the performance test of the fusion speed measurement control system.By comparing the data before and after fusion,the optimization parameters of the control system are analyzed.