A mobile robot positioning method based on an improved ORB algorithm

A mobile robot, positioning method technology, applied in computer parts, instruments, computing and other directions, can solve the problems of image scale change not robust, FAST feature not scale invariance, cumulative error increase and other problems, to achieve good results. Real-time performance and feature matching accuracy, improve autonomous positioning accuracy, and reduce cumulative errors

Inactive Publication Date: 2019-06-18
CHINA JILIANG UNIV
View PDF0 Cites 9 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0002] In recent years, with the development of artificial intelligence technology, mobile robots have been widely used. It liberates people from heavy physical labor and effectively saves labor costs. Mobile robots need to obtain information in real time during their long-distance travel. Positioning information, commonly used mobile robot navigation methods include magnetic navigation, inertial navigation, visual navigation, etc. Magnetic navigation has high reliability, but it is costly and difficult to maintain; inertial navigation is a common navigation method for mobile robots, because it will lead to accumulation The error increases infinitely and is not suitable for long-term precise navigation. Currently, the commonly used mobile robot navigation method is a grid-based motion statistics combined navigation method. Although this navigation method has high stability, it has a large cumulative error
[0003] The ORB algorithm is a feature point detection and description algorithm based on visual information. It uses the FAST (features from accelerated segment test) algorithm to detect a certain feature point and the pixel value in the surrounding area. The area is generally a circular area. , the ORB algorithm uses the BRIEF (binary robust independent elementary features) algorith

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 mobile robot positioning method based on an improved ORB algorithm
  • A mobile robot positioning method based on an improved ORB algorithm
  • A mobile robot positioning method based on an improved ORB algorithm

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0045] see Figure 1-3 , a mobile robot positioning method based on the improved ORB algorithm, comprising a mobile robot and a computer, the experimental operating environment of the computer is Intel(R) Core(TM) I5-4590M 3.3GHz 4GB, VS2013 and Opencv3.2, including the following steps:

[0046] (1) Input image pair: the mobile robot collects images in real time through the camera, and transmits the images to the computer for image processing in real time;

[0047] (2) Image gridding: Utilize the GMS algorithm to adopt the grid to divide the image into non-overlapping units of G=20*20;

[0048] (3) ORB descriptor: use the ORB algorithm to detect and extract the feature points, and then use the BRIEF algorithm to describe the feature points to obtain the descriptor;

[0049] (4) Bayesian visual modeling;

[0050] (5) Network weighted statistics;

[0051] (6) Network statistical value matching: Using the GMS feature registration algorithm based on the scoring framework, due t...

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 invention discloses a mobile robot positioning method based on an improved ORB algorithm and belongs to the technical field of positioning technology of mobile robots. and the method comprises a mobile robot and a computer, and steps of inputting of image pairs: the mobile robot acquires images in real time through a camera and transmits the images to the computer for image processing in realtime; Image gridding: using a GMS algorithm to segment the image into non-overlapping units with G = 20 * 20 by using a grid; ORB descriptor: detecting the extracted feature points by using an ORB algorithm; According to the invention, feature points with scale invariance can be extracted by using an SIFT algorithm; and finally, the matching quality is remarkably improved by utilizing a GMS feature registration algorithm based on a scoring framework, the real-time performance and the feature matching accuracy are better, the odometer accumulation error in autonomous navigation is effectively reduced, and the autonomous positioning precision of the mobile robot is improved.

Description

technical field [0001] The invention relates to the technical field of mobile robot positioning, and more specifically, relates to a mobile robot positioning method based on an improved ORB algorithm. Background technique [0002] In recent years, with the development of artificial intelligence technology, mobile robots have been widely used. It liberates people from heavy physical labor and effectively saves labor costs. Mobile robots need to obtain information in real time during their long-distance travel. Positioning information, commonly used mobile robot navigation methods include magnetic navigation, inertial navigation, visual navigation, etc. Magnetic navigation has high reliability, but it is costly and difficult to maintain; inertial navigation is a common navigation method for mobile robots, because it will lead to accumulation The error increases infinitely and is not suitable for long-term precise navigation. Currently, the commonly used mobile robot navigation...

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
IPC IPC(8): G06T7/73G06T7/33G06K9/46G06K9/62
Inventor 郑恩辉王谈谈徐玲
Owner CHINA JILIANG UNIV
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