JUSTIFICATION OF THE LIST OF FACTORS FOR SELECTING A WEEDING ROBOT MODEL

Abstract

The problem of weeds is one of the most pressing issues in modern agriculture. Traditional technologies, which involve the use of large amounts of chemical agents, have become a serious threat to global ecological systems. Moreover, some weed species have developed resistance to various herbicides, reducing the effectiveness of chemical control measures. This situation necessitates the adoption of innovative approaches to organizing technological processes for efficient weed elimination. Analysis of current research has shown that the global scientific community considers the introduction of robotics in agriculture a highly promising and relevant direction for further development. The deployment of robots in agriculture in countries such as the United States, the Netherlands, and China already contributes to resolving multiple pressing problems. Specifically, it allows farmers to reduce production costs, address labor shortages, maintain consistently high product quality, and improve overall working conditions. Considering these factors, the National University of Water and Environmental Engineering conducts applied scientific projects aimed at developing and testing robots for various agricultural tasks. The author has carried out a series of works on developing a specialized robot for targeted weed removal. This article presents the results of analyzing current research focused on designing and implementing advanced technologies for weed detection and control based on robotic systems. The analysis serves as the foundation for the conceptual design of a practical robot model. Additionally, the article outlines the results of expert evaluation of key factors determining the choice of a weeding robot for a specific agricultural enterprise. Effective selection of a robot for a particular farm requires a systematic scientific approach to organizing the weed elimination process, considering all quantitative and qualitative factors, many of which may not directly depend on the manufacturer. The results obtained can be used by agricultural producers to make a well-justified choice of robot and efficiently organize weeding technologies in a sustainable and productive manner.