Study On The Key Technology Of Visual Navigation For Agricultural Automation Equipment

Agricultural automation equipment is of great significance for the realization of “precision agriculture” technology.The visual navigation of agricultural automation equipment is a hot research topic in the field of agricultural machinery.In this thesis,the key technology of the visual navigation of agricultural automation equipment is studied systematically,such as image processing,path planning,navigation information obtaining and so on.Firstly,in this thesis,a method is presented to extract visual navigation baseline based on the image features of farmland,in which the weighted average method,improved maximize between-class variance and small area method are used to preprocess the original image.Then the location of center points of the navigation path is determined by maximum difference method of column coordinate,after which the invalid center points are removed according to the distribution regularity of the center points.The navigation baseline is generated by using the improved Hough transform and the least square method.Secondly,based on improved ant colony algorithm,the mathematical model is established which is the objective function acquired with shortest working time.At the same time considering the parameters of the area of the actual farmland,the turning path is optimized.Finally,in order to build the relationship between the visual information of the camera and the three dimensional space,the cameras are calibrated by the Zhang’s calibration method,and stereo calibration method is implemented for the two cameras.With the internal and external parameters of cameras,the geometric relationship between the agricultural automation equipment and navigation baseline is acquired.The navigation information parameters are obtained,including the deviation distance and angle deviation between agricultural automation equipment and navigation baselines,to realize the visual navigation of agricultural automation equipment by the increasing PID control algorithm.Results of experiments show that the key technology of visual navigation presented in this thesis is effective and has applicable value.