A Method for Industrial Robots to Grasp and Detect Parts of Instrument under 3D Visual Guidance

Abstract

Guiding industrial robots to complete grasping tasks through machine vision is an important part of achieving autonomous robot operation. This article explores the control method of industrial robots under 3D vision, focusing on the feature that two-dimensional vision can only perform color and pose recognition but lacks depth recognition. Firstly, a high-precision point cloud registration calibration matrix solution method is proposed. Then, an improved recognition model is designed to address the issue of how vision guides robots to grasp and detect. This model integrates feature extraction and object detection modules, and describes the parameters of each module. Finally, the effectiveness of the proposed method is verified in the assembly scene of gas instruments. Finally, experimental results show that, the method proposed in this article can limit the grasping accuracy to within 2 millimeters in guiding robots to grasp detection scenes, achieving the expected effect.