Geometric Positioning and Color Recognition of Greenhouse Electric Work Robot Based on Visual Processing

Abstract

With the continuous development of science and technology, industrial production technology is also constantly developing, and production efficiency is also constantly improving. Greenhouse electric working robots are industrial production tools with automatic control technology as the core, which affects the quality of industrial products and thus affects the profitability of the factory. According to the set programming work, the greenhouse electric working robot can realize the reproduction production and reduce the workload of the workers. In today’s era, the industrial production steps are more complicated, the production process is more flexible, and the robot’s unchanging posture and movement cannot meet the needs of modern industry, which restricts the development of the factory. In order to better complete the work of industrial robots, it is necessary to study the geometric positioning and color recognition of industrial robots based on machine vision to improve the working efficiency of industrial robots. This paper established an active positioning machine vision system for precise positioning of robot parts greenhouse electric working stations. The matching method using image processing and feature recognition area based on the shape of the binding phase combines the threshold shape criterion to identify object features. The experiments prove that the method can quickly and accurately obtain the object boundaries and centroid calculations and identification data, the robot kinematics combined with real-time motion control of the robot in order to eliminate this error, meet the requirements of the industrial robot self-aligned.