Apple harvesting robot under information technology: A review

Weikuan Jia,Yan Zhang,Yuanjie Zheng,Dean Zhao,Jian Lian,Chengjiang Li

doi:10.1177/1729881420925310

Abstract

It has been more than 30 years since the French pioneered the research of the apple harvesting robot, and with the joint efforts of scholars all around the world, a variety of prototypes have been developed. However, the existing apple harvesting robot prototype is still in the experimental research stage because of its low harvesting efficiency. With the help of information technology, the related research has ushered in a milestone development, and it is full of opportunities and challenges for apple harvesting robotic researchers. In this article, it briefly introduced the development history, structure, and composition of apple harvesting robots and the operation process, which makes readers have a clear understanding of apple harvesting robot and its harvesting principle. Then systematically summarizing the research results of apple harvesting robots both at domestic and at foreign, we carried out in following three aspects: rapid and accurate recognition and positioning of target fruit, all-weather operation mode, and application of intelligent computing theory in apple harvesting robots, and it analyzes the research progress of apple harvesting robot in detail. The results show that improving the harvesting efficiency is the key and hot spot for the research on apple harvesting robots. Under the impetus of information technology, how to achieve fast and accurate recognition of the fruits of multienvironment and multiple information, obtain reasonable path planning, and further optimization of control strategies are all important research directions.

Highlights

Apple ranks second in the global fruit production rankings over grapes, according to the statistics of the Food and Agriculture Organization
Because some fruits and vegetables are harvested with strong seasonality, 1 School of Information Science and Engineering, Shandong Normal University, Jinan, China
Fu used the RG color model to segment the nighttime images of the collected kiwifruit and detected the target fruit using the Canny operator; the experimental results showed that the optimal illumination of the artificial light source was 30–50 lx and the recognition rate was 88.3%

Summary

Introduction

Apple belongs to the heliotrope temperate deciduous tree; due to its crisp fruit and rich nutrition, it is known as the “the crown of fruit.” Because of its high water solubility and easy absorption by the body, it is called “living water.” Apple ranks second in the global fruit production rankings over grapes, according to the statistics of the Food and Agriculture Organization.

Results

Conclusion