Dynamic planning method for picking sequence of sphere-like fruits

Abstract

The invention discloses a dynamic planning method for a picking sequence of sphere-like fruits. A dynamic harvesting perception method for planning perception points and picking points together is designed. After a mechanical arm finishes picking or perception each time, weight updating is carried out through judgment, and a weight updating rule of fruit depth information is added. According to the dynamic harvesting perception picking sequence planning method, the perception points and the picking points of picking are combined on the basis of the dynamic planning method, and compared with atraditional experience-based picking sequence planning method, a global perception method, a batch sensing method and the like, the planned picking sequence is short in picking path and high in real-time performance, and the picking efficiency and the picking success rate of a picking robot are improved. The designed dynamic harvesting perception picking sequence planning method is improved, frontand back fruit picking sequence planning based on a three-dimensional space is added, fruit damage caused by the picking sequence is avoided, and the fruit picking damage rate is reduced.

Description

technical field [0001] The invention belongs to the field of robot fruit picking, in particular to the picking of spherical fruits, and is used in fields such as plant greenhouses and plant factories where the fruit quantity is large and the fruit distribution is uneven, and picking robots are required to independently complete picking tasks. Background technique [0002] With the increase in the scale of plant greenhouses and plant factories and the increase in labor costs, the intelligentization of fruit and vegetable picking and harvesting has become an urgent demand for agriculture in various countries. With technological breakthroughs in the fields of computer and image processing, fruit and vegetable picking robots have developed rapidly. For example, the citrus picking robot developed by the University of Florida in the United States, the bell pepper picking robot developed by Ben Ha-Gurion University of the Negev in Israel and applied to commercial greenhouses, and t...

AI Technical Summary

Problems solved by technology

[0004] In order to overcome the problem of low picking efficiency and easy fruit damage in the currently commonly used picking method based on experience from top to bottom and from left to right, the present invention improves the overall fruit harvesting speed, improves the success rate of fruit picking, and reduces fruit damage. From the perspective of efficiency, a dynamic programming method for the picking sequence of spherical fruits is proposed.

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