Visual capture method and device based on depth image and readable storage medium

Abstract

The invention discloses a visual capture method and device based on a depth image and a readable storage medium. The method comprises steps that a point cloud image is acquired through a depth cameraKinect, the acquired point cloud image is segmented through an RANSAN random sampling consensus algorithm and an Euclidean clustering algorithm, and an identification-needing target object is acquiredthrough segmentation; 3D global characteristics and color characteristics of the object are respectively extracted and are fused to form a new global characteristic; off-line training of a multi-class support vector machine classifier SVM is carried out through utilizing the new global characteristic of the object, category of the target object is identified through utilizing the trained multi-class support vector machine classifier SVM according to the new global characteristic; then the category and the grasping position of the target object are determined; and lastly, according to the category of the target object and the grasping position of the target object, a manipulator and a gripper are controlled for grasping the target object to the specified position. The method is advantagedin that the target object can be accurately identified and grasped.

Description

technical field [0001] The present invention relates to the field of robot visual grasping, in particular to a depth image-based visual grasping method, device and readable storage medium. Background technique [0002] Robot visual grasping is one of the very important research directions in the field of robot research. This importance is mainly reflected in its wide range of application scenarios. Not only in the factory assembly line, it is necessary to use a large number of mechanical arm visual grasping to complete the assembly work. Moreover, in daily service robots, robotic arm vision grasping is also required to complete daily work. More importantly, with the rise of online shopping and the Internet of Things, it is becoming increasingly important to intelligently classify and select items in warehouses. At the same time, robotic arm vision Grasping also involves a multidisciplinary approach, including disciplines such as automatic control science, image processing, m...

AI Technical Summary

Problems solved by technology

Although the use of three-dimensional image information for object recognition can make good use of the three-dimensional information of the object such as shape features, it cannot take advantage of the advantages of image processing methods and the use of object texture information, and it will also cause misjudgment of objects with similar shape features. affect the accuracy of object recognition

Images