A grabbing control method of a robotic arm based on binocular vision

A technology of binocular vision and control method, which is applied to manipulators, program-controlled manipulators, manufacturing tools, etc., can solve problems such as low precision and difficulty in extracting cross-section circles, so as to overcome the influence, stabilize the center of gravity, and improve the accuracy of detection. Effect

Active Publication Date: 2022-03-01
DALIAN UNIV OF TECH
View PDF5 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

In order to solve the problems of difficulty in extracting the cross-section circle and low precision, the present invention proposes the method of using foreground extraction to obtain the apex of the cross-section arc of the target object, and estimate the posture of the target object with the coordinate difference of the apex, and finally control the manipulator to be as flexible as a human hand. grab target

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • A grabbing control method of a robotic arm based on binocular vision
  • A grabbing control method of a robotic arm based on binocular vision
  • A grabbing control method of a robotic arm based on binocular vision

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0062] The present invention will be further described below in conjunction with accompanying drawing.

[0063] Such as figure 1 As shown, a robot grasping control method based on binocular vision includes the following steps:

[0064] Step 1. Build the experimental platform. Install the binocular vision camera at 1-1.5m directly above the experimental platform, start the binocular vision camera, start the kinova robotic arm and load the left and right robotic arm model urdf, which describes the kinova robotic arm The position and posture relationship of each joint, where the left robotic arm is installed on the left-hand side of the horizontal desktop, its bottom coordinate system is defined as left, the right robotic arm is installed on the right-hand side of the horizontal desktop, its bottom coordinate system is defined as right, and the distance between the left and right robotic arms is 0.8 -1.2m. The root coordinate system is defined as root in the middle of the left ...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

Abstract

The present invention relates to the technical field of kinova mechanical arm and ZED vision, a kind of control method of the mechanical arm grasping based on binocular vision, comprises the following steps: (1) experimental platform is built, (2) the position and posture when the target object is placed obliquely Recognition, (3) Recognition of the position and posture of the target when it is placed horizontally, (4) The end effector of the robotic arm recognizes and grabs the target object, (5) The robotic arm reaches the specified joint angle state after grabbing the target. The present invention has the following advantages: First, the angle deviation between the direction vector and the coordinate axis plane is within -5 to +5 degrees when estimating the attitude angle of the target object, and the detection accuracy is greatly improved. Second, the use of color + shape can avoid the interference of the same or similar color interference items on the target object recognition. The third is to set the dual robotic arms to grab the left and right target objects, and finally obtain the effect of the left and right robotic arms grabbing the target object posture.

Description

technical field [0001] The invention relates to a binocular vision-based grasping control method for a robotic arm, which belongs to the technical field of kinova robotic arm and ZED vision. Background technique [0002] Binocular vision pose measurement is an important target pose method, but it is difficult to measure the pose of an obliquely placed object. Some existing methods include: circle extraction method and feature point extraction method. [0003] Circular section extraction method: the existing method is to use three industrial CCD cameras to extract the center of the upper and lower sections of the cylindrical target, define a coordinate system, and calculate the angle between the line connecting the two section centers and the coordinate system to describe the position Attitude, the accuracy of this method is greatly affected by the shape of the target, and the center of the occluded circular section is not easy to extract. [0004] Feature point extraction m...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
Patent Type & Authority Patents(China)
IPC IPC(8): B25J9/16
CPCB25J9/1612B25J9/1602B25J9/1697B25J9/1648B25J9/1664
Inventor 王东杨冬董永祥连捷
Owner DALIAN UNIV OF TECH
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap