Meat pigeon precise feeding method based on mixed deep neural network

Abstract

The invention discloses a meat pigeon accurate feeding method based on a mixed deep neural network, which is realized by a feeding robot consisting of a carrying chassis vehicle navigation module, a mechanical arm feeding module, a blanking module and an operation control module, and can mix a plurality of deep neural networks for operation control, so that intelligent and mechanical operation is realized, and the feeding efficiency is improved. Path division and pigeon growth state recognition are performed by means of a visual recognition system, closed-loop control among chassis autonomous navigation, mechanical arm feeding operation and blanking unit precise control blanking links is realized by adopting a closed-loop control system, a large amount of manual labor is not needed, intelligent and mechanical autonomous operation can be realized, and the working efficiency is improved. Meanwhile, the feeding amount can be controlled according to the number, the size and the current activity state of the pigeons, the pigeons can eat less and many meals, the pigeons are prevented from eating picky food, the feed conversion ratio of meat pigeon breeding is increased, and then scientific breeding of the pigeons is achieved.

Description

technical field [0001] The invention relates to the technical field of meat pigeon breeding, in particular to a precise feeding method for meat pigeons based on a hybrid deep neural network. Background technique [0002] The large-scale breeding of meat pigeons in my country was first seen in the early 1980s, and it was improved by introducing foreign excellent meat pigeon varieties while developing. Based on this, the large-scale breeding of meat pigeons in my country has been continuously formed. From south to north, from the coast to the inland, more and more herdsmen have joined the army of meat pigeon breeding. As of now, there are more than 30 breeds of meat pigeons in China. By the end of 2020, the stock of breeding pigeons in my country will be about 1.34 million pairs, a year-on-year increase of 10%, which is the largest stock since 2017. From historical data, since 2018 Since September, except for a few months, the production capacity of meat pigeons has basically ...

AI Technical Summary

Problems solved by technology

[0004] Most of the existing livestock and poultry feeding robots are fed in fixed areas, not mobile feeding robots, which lack convenience; livestock feeding robots often spray marks or install sensors on large livestock, and then drive the livestock to In the feeding area, accurate feeding can be realized through sensor data or image processing data. In the breeding environment where there is no precision feeding, they are usually fed regularly and quantitatively, which lacks precision and easily leads to waste of feed

To sum up, at present, in the cage environment of poultry, especially the large-scale cage environment of meat pigeons, the feeding task is still mainly manual, which is labor-intensive and boring.

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