Non-contact Storage Classification Based on Mechanical Arm in the Context of Prevention and Treatment of COVID-19

Abstract

COVID-19 has become a global infectious disease, which has a high transmission rate, a wide transmission range, and a variety of transmission modes. Therefore, to reduce the transmission efficiency of COVID-19, human beings try to reduce the manpower ratio to create a non-contact environment in the industry. Therefore, a new model is proposed in this paper. This new model aims to be applied to storage classification in the context of the prevention and treatment of COVID-19 by using the mechanical robot arm. This model will use the UR3 robot arm, Logitech C300 web camera, and OpenCV public repository to implement the computer vision algorithm, and forward and inverse kinematics analysis. This model can successfully implement non-contact storage classification. Through the real experiment, this paper has a good application prospect. It gives a new solution for future research and experiment. In addition, in the summary and outlook part of this paper, new research directions in the future are given.