Research On Plant’s Three-dimensional Information Detection And Visual Servo Controlling Technology

Sensing technology is the basis for precision agriculture. Detect spatial information of the target, which can be used to control the the actuator, is needed in automated agricultural production operations. Machine vision is considered to be a potential, low failure and risk and contactless measuring technology which makes it suitable for being applied to agricultural circumstances. Most of the agricultural production tasks accompany the relative motion between the objects and the actuator A method of the plants’three-dimensional information detecting based on the translation of the camera and a visual servo positioning control strategy directly based on the image features was proposed, which was combined used the motion relationship and the machine vision technology. The main research contents and conclusions were as follow:(1) Plant image green information segmentation method was studied based on different color space. A set of sample images’ green information was extracted manully. Plant defective segmentation percentage, plant exceeded segmentation percentage, plant segmentat error percentage, as well as the image processing time was used as the performance parameters of different segmentation algorithm. A green information segmentation method which combined the fixed threshold segmentation under HSV color space and threshold segmentation by Otsu for the image data after the operation of Exceed Green minus Exceed Red (3G-2.4R-B) was designed.(2) The corresponding points matching algorithm was studied for images acquired from different views. The sum of absolute defferences (SAD) was choosed as the mearement error for the area maching. The maching algorithm was studied based on the experimentions which were operated on different image data, with different template size and different template types. A difference matching algorithms strategy was designed depending on the position of the matching points.(3) Plant three dimensional information detection algorithms were studied when the camera was translated in the X-Yplane. The experimentions was done with the crops as the subjects in order to find out the influence on the detected results of the plant three dimensional information while the camera was under different motion parameters and different position parameters. According to the experiment, the direction of movement of the camera has little effect to the measurment results, and there would be get better results when the moving distance of the camera becoming larger and the distance was closer between the camera and the object.(4) The depth information between target and the camera was studied while the camera was moving along the optical axis. The distance between the equivalent plane of the target in the direction of projection of the camera and the camera center would be calculated when the camera was moving along the optical axis. A standard target and a potted plant was chose as the subjects in order to find out the measurement performance under the different distance between target and the camera and the different distance of the camera moved. As a result, the larger the moving distance of the camera, the closer between the camera and the target object, the better of results of the measurement. (5) A visual servo positioning control strategy based on the method depth information measurement between target and the camera when the camera was moving along the optical axis. Three image features was directly used to control the moving and positioning of the actuator in the three directions of space. A Cartesian robot system was set up with two electric translation platforms driver by two-phase stepper motor and an electric cylinder driver by DC motor. The experiments of target’s three dimensional measurements and visual servoing control of the camera relative to the plant was done based on the robot system. A satisfying result was abtained through the experiments.Research laid the foundation for machine vision inspection and the actuator’s visual servoing in agricultural production. Meanwhile this tudy has important value to automate spraying, harvesting, transplanting and other agricultural production operations which based on hand-eye approach.