Abstract:
Abstract: Considering mechanical vibration and other external factors, there are two main aspects influence the plug tray position in the process of mechanical transplanting seedlings from plug tray to nutrition bowl. One is that the plug tray is skew or the center point of it has a displacement when the plug tray was placed on the manipulation platform or the conveyor belt area. The other is that the plug tray is raised partly which attributes to the soil adhesion at the bottom of it or the soil of previous plug tray accidentally slip onto the platform. Therefore, transplanting error can appear or fingers inserted too deep to wear out plug tray when manipulator walks according to the standard coordinates. These affect the transplanting quality, and sometimes even lead to failure of the whole plug tray transplant. In order to solve the problems and to provide precision coordinates of plug tray, we studied plug tray accurate localization method using binocular stereo vision. Firstly, we proposed the overall method of mechanical transplanting plug tray localization based on binocular stereo vision and acquisition of binocular images. Second, we located two-dimensional plane plug tray by calculating center point coordinates and deviation angles using images obtain from monocular camera. For calculations of center point, we used pixel labeled algorithm based on recursive method of connecting area in binary images, and angles adopted Radon transformation in edge detection images. Then, we located three-dimensional stereo plug tray by acquiring the coordinates of pairs of matching points that adopted Scale Invariant Feature Transform (SIFT) feature matching algorithm using pairs of images obtained from binocular cameras. Meanwhile, considering the factors of plug tray material and improvement the speed of three-dimensional reconstruction, we proposed a method of regional integrated matching points. Finally, we adopted Zhang camera calibration method, and used 8×8 checkerboards to calibrate stereo cameras. Cooperated with binocular camera calibration results, we rebuilt the three-dimensional coordinates of regional integrated matching points, and reconstructed plug tray spatial location by combining the results of two and three dimensions. Experimental results indicated that our plug tray localization method based on binocular stereo vision was able to reconstruct plug tray space posture veritably. We randomly selected 10 plug trays to do two-dimensional plane localization experiment. From the perspective of angle, we observed that the angle relative errors between detected and measured were in the range of -0.51° to +0.53°, in which the small angle had a large percentage of relative error. The reason for that was the Radon transform results were integer. From the perspective of center point coordinates, we observed the relative errors of horizontal and vertical coordinates between detected and measured were in the range of -7 to +7 and -6 to +7 pixels, respectively. The main source of error was the method taking the two-dimensional projection problem into account only. Angle and center point coordinates errors were within the acceptable range. We selected No.1 plug tray to do three-dimensional stereo localization experiment. We adopted SIFT feature matching algorithm matching binocular images (images size are 736 pixels×480 pixels),and got 147 pairs of matching points. When optimize the matching points by using RANSAC(RANdom SAmple Consensus) method, the number of matching points pairs dropped to 55. We reconstructed eight pairs of integrated matching points in the 2×4 area of world coordinates, seven of which the three dimensions relative errors between detected and measured were in 2 mm, and one of which was in 4.6 mm. In summary, our application algorithms were mature, the whole method was reliable, and satisfied the requirements of practical mechanical transplanting application processing.