Automatic plug seedling transplanting path optimization method based on artificial ant colony

Abstract

The invention discloses an automatic plug seedling transplanting path optimization method based on an artificial ant colony. The method comprises the steps that the health conditions and position information of plug seedlings in seedling trays with plug holes to be filled with seedlings and plug seedlings in transplanting seedling trays are determined through the machine vision method, and a seedling tray matrix is generated, positive and negative node numbering is carried out, and the concentration of pheromones is initialized; next access nodes are selected by artificial ants through the roulette method, accessed nodes are added into a taboo table so that the nodes will not be repeatedly accessed, and access paths of the artificial ants are recorded to obtain the length of the shortest path and the numbering sequence of all the nodes of the shortest path; the pheromones are comprehensively updated, and the taboo table is cleared after updating is finished; the steps are repeatedly executed, and the shortest path of each turn of access of the artificial ants is recorded to obtain the shortest path. By means of the method, the motion path of a transplanting claw can be effectively shortened in the process of filling the plug holes with seedlings, working efficiency is improved, an excellent optimization effect is also achieved in the process of dealing with a large number of empty plug holes, and a signal empty plug hole can be dealt with as well.

Description

technical field [0001] The invention relates to a method for optimizing a transplanting path of plug seedlings, in particular to a method for optimizing an automatic transplanting path of plug seedlings based on artificial ant colonies. Background technique [0002] The seedling rate of industrial plug-in trays is generally between 80% and 95%. In addition to ungerminated and missed holes in the plug-in trays, there are also poor-quality and unhealthy pot seedlings, which is not conducive to subsequent mechanized operations and factory sales. Therefore, it is necessary to remove unhealthy seedlings and replenish seedlings before the plug-in seedlings leave the factory. The facility agriculture automation pot seedling transplanting machine detects the health status and location information of pot seedlings through machine vision, and realizes seedling replenishment and sparse planting operations through the transplanting system, replacing traditional manual transplanting, the...

AI Technical Summary

Problems solved by technology

In the existing research, the optimization effect of the greedy optimization method is not very obvious. The genetic optimization method is better when dealing with a small number of holes, but the effect is not ideal when the number of holes is large, and it cannot handle the situation when there is only one hole.

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