Research On The Positioning And Picking Of Cucumber Picking Robot

In the production of fruits and vegetables production,the picking work is time-consuming and laborious,requires a lot of labor,and costs more.With the aging population and the development of urbanization,The agricultural labor force is becoming less and less,and the cost of picking jobs has increased greatly.At present,the agricultural production in our country is moving towards the direction of intelligence,precision,diversification and scale.Studying agricultural machinery with high intelligence and agricultural robots can effectively solve the problems of insufficient agricultural labor force,increase in production cost and improve work efficiency.It can also improve the working environment,prevent long-term work,pesticides,fertilizers and other injuries to the human body,which is of practical significance.In this paper,the cucumber variety "Ji Za-4" was studied.After understanding and analyzing the cucumber’s physical characteristics,a 4-DOF cucumber picking robot prototype was made,and research on the acquisition of the coordinate value of the target feature point,the overall control system of the picking manipulator was carried out.The main research contents and results are as follows:(1)According to the actual picking environment,the overall mechanical structure of cucumber picking robot was designed,including: designed and made a 4-DOF manipulator to ensure that the motion of the manipulator is flexible and stable.,the camera bracket was designed and manufactured so that the camera can follow the movement of the waist joint of the manipulator to obtain the current picture.According to the cucumber’s physical characteristics,the end effector had been designed and made,according to the relationship between the length of the cucumber fruit and the length of the cucumber fruit stem,the grasping feature point of the fruit was set at 1/4 distance from the top of the cucumber fruit,and the cutting blade distance from finger is 5.2 cm,experiments show that the end effector cutting success rate was 95%,showed the feasibility of the design method.(2)How to get the coordinate value of feature point through image processing was studied.By comparing commonly used color models,the H and S component thresholds in the HSV color model were set,to segment the target fruit.Apply MATLAB to process the segmented color image to get the minimum bounding rectangle of the target fruit,mark the centroid pixel coordinates and convert to the pixel coordinate values corresponding to the feature points.According to the identification of cucumber fruit,20 groups of samples were tested,the recognition success rate was 80%,and the error of the obtained coordinate value in Y direction could meet the picking conditions.The method and principle of obtaining the spatial coordinates of feature points are introduced in detail.Error experiments were performed on the depth distances obtained with the Kinect sensor.In the 20 sets of sample data,the error range is basically between 0-2 mm.It is verified by experiments that the error generated by the obtained depth value has little effect on the actual extraction result.(3)Research on the design of picking robot identification and control system was performed.For Manipulator’s overall transmission,selected the appropriate drive and drive structure.The control system of picking manipulator based on PCI bus control,the feature point recognition and acquisition system based on Kinect for Windows SDK and MATLAB,and the lower computer control system developed by STC89C52 microcontroller were designed.For these three parts,the hardware and software are designed,design and manufacture of servo control circuit,the end of the actuator control circuit,image processing interface and the manipulator control interface.(4)Under laboratory conditions,for the design of picking robot prototype,the simulation experiment of positioning and picking were carried out.First,test the performance of the manipulator,experiments show that manipulator has better position control accuracy and speed control accuracy,it can meet the requirements of the manipulator movement.Secondly,in the laboratory conditions,the simulation experiment of the eigen-point space coordinate error was carried out,experiments show that the errors in the Y-axis direction between the spatial coordinate values of the feature points obtained by the image processing and the actual measured spatial coordinate values are mainly concentrated in the range of 3mm-5mm;the errors generated in the Z-axis direction are mainly concentrated in the range of 2mm-5mm.The errors generated in both directions will not have a great impact on the picking and can meet the requirements of grasping.The simulation experiment verifies the feasibility of using the method of obtaining the spatial coordinates of feature points.Finally,the simulation picking environment was set up in the laboratory and the simulation picking experiment was carried out according to the picking effect of the manipulator and the end effector.By analyzing the results of 40 groups of simulated picking experiments,we can see that the success rate of the manipulator positioning the end effector to the designated feature point was 92.5%,the success rate of the end effector picking the target fruit was 82.5%,the average time taken to complete the whole process of picking the target fruit with the two parts is about 15.28 seconds;the picking robot runs stably and can work well with the control system to achieve the complete picking of the fruits.