Fine-adjustment positioning method of fruit and vegetable picking point

Abstract

The invention discloses a fine-adjustment positioning method of a fruit and vegetable picking point, which comprises the following steps of: collecting close-range position information of a fruit and vegetable picking region by utilizing a picking robot to acquire first positioning data; controlling a picking terminal executer to move to a space point according to the first positioning data; collecting the current image by a camera and processing the collected image to acquire an image coordinate of a picking point; converting the image coordinate of the picking point into space three-dimensional coordinates of the picking point; and controlling the picking terminal executer to move from the current position to a position corresponding to the space three-dimensional coordinates according to the space three-dimensional coordinates of the picking point by a picking mechanical arm controller and positioning the picking point. By secondary precise positioning, the invention finely adjusts and corrects the terminal motion error of the mechanical arm and enables a robot target positioning system to form a closed ring so as to accurately position picking division points, accurately cut and pick cucumber fruits, and improve the working reliability of the picking robot.

Description

technical field [0001] The invention relates to the field of agricultural robots, in particular to a method for fine-tuning and locating fruit and vegetable picking points. Background technique [0002] In recent years, the research on fruit and vegetable picking robots in the field of modern agricultural technology at home and abroad has become a hot spot, but there is still a considerable gap in the real replacement of humans to complete the picking tasks. There are two most important issues: one is that the picking robot works in an unstructured environment. Due to the influence of unstable factors such as natural light and biodiversity, the target and the background are superimposed with multiple information, the similarity of the color of the fruit and the stem and leaf, Both have become difficulties in the extraction of fruit feature information; second, the spatial positions of the picking objects are randomly distributed and the individual differences are large, whic...

AI Technical Summary

Problems solved by technology

In recent years, the method of using close-range secondary precise positioning to improve picking accuracy has begun to be studied. E.J.VAN in the Netherlands installed a visual sensor at the end of the picking robot for close-range positioning of the target, but its 3D reconstruction algorithm is complicated and time-consuming. Meet the real-time requirements of robots

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