Agricultural robots for fruit harvesting in horticulture application

Author:

Barbashov N N,Shanygin S V,Barkova A A

Abstract

Abstract For the development of the agricultural industry, the urgent task of designing robots capable of efficiently harvesting crops is being set. To do this, it is necessary to ensure the high quality of the algorithm of the computer vision system for determining the boundaries of fruits and the degree of their ripeness. Differences in weather conditions and illumination of a fruit tree have a significant impact on the operation of such an algorithm. It is shown that due to the introduction of neural networks into machine vision systems, the speed of fruit detection has significantly increased. The development of robots for harvesting fruits will allow replacing heavy physical labor of a person, as well as reducing the percentage of crop shortage.

Publisher

IOP Publishing

Subject

General Engineering

Reference9 articles.

1. Analysis of the main trends in the development of the waste management system in Russia: problems and prospects;Zukova;Ecology and industry in Russia,2020

2. Experimental and calculation study of diesel generator performance in transient conditions;Kuznetsov;Journal of engineering for gas turbines and power,2018

3. Stabilization of a rigid rotor in conical magnetic bearings;Ovsyannikova;Problems of mechanical engineering and machine reliability,2020

4. Methodological foundations for choosing the materials for gears according to wear resistance criteria;Polyakov;Journal of Machinery Manufacture and Reliability,2019

5. Influence of centrifugal forces on oil flow in journal bearing of planetary gear;Temis;Journal of fluids engineering Journal of fluids engineering, transactions of the American society of mechanical engineers,2018

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