Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

VI-SLAM closed-loop detection method based on inertial navigation attitude track information assistance

A closed-loop detection and closed-loop technology, applied in the field of positioning, can solve problems such as difficult to distinguish similar scenes, and achieve the effect of improving accuracy and computing efficiency

Active Publication Date: 2019-11-19
CENT SOUTH UNIV
View PDF7 Cites 16 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0009] The purpose of the present invention is to provide a closed-loop detection method that can take into account the correct rate (solve the problem that it is difficult to distinguish similar scenes) and computational efficiency

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
  • VI-SLAM closed-loop detection method based on inertial navigation attitude track information assistance
  • VI-SLAM closed-loop detection method based on inertial navigation attitude track information assistance
  • VI-SLAM closed-loop detection method based on inertial navigation attitude track information assistance

Examples

Experimental program
Comparison scheme
Effect test

Embodiment

[0057] The relevant names of this embodiment are explained as follows:

[0058] Closed-loop detection: refers to the ability of the robot to recognize that it has reached a certain scene and make the map closed-loop. To put it simply, when the robot turns left or right to build a map, it can realize that a certain place has been visited by "I", and then match the map generated at this moment with the map just generated.

[0059] TF-IDF: is a statistical method for evaluating the importance of a word to a document set or a document in a corpus. The importance of a word increases proportionally to the number of times it appears in the document, but decreases inversely proportional to the frequency it appears in the corpus.

[0060] SLAM: Instant positioning and map construction, or concurrent mapping and positioning. The problem can be described as: put a robot in an unknown position in an unknown environment, is there a way for the robot to gradually draw a complete map of th...

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 provides a VI-SLAM closed-loop detection method based on inertial navigation attitude track information assistance, which comprises the following steps: providing an attitude of a movingobject through inertial navigation, calculating a rotation angle of each frame of image relative to a previous frame of image, and obtaining a key frame based on the rotation angle; then based on theinertial navigation track, carrying out particle filtering on the basis of the key frame, and obtaining candidate closed-loop frames with loose conditions; creating a bag-of-words model, and performing feature quantification on the candidate closed-loop frame and the current frame by using a visual dictionary tree; and finally, performing frame-by-frame matching on the current frame data and thecandidate closed-loop frames by using an improved pyramid TF-IDF score matching method, thereby extracting a closed loop. The method has the advantages that compared with a traditional bag-of-word model method, the accuracy can be effectively improved, and the calculation efficiency can also be improved.

Description

technical field [0001] The present invention relates to the technical field of positioning, in particular to a VI-SLAM closed-loop detection method assisted by inertial navigation attitude track information. Background technique [0002] VISLAM technology plays an important role in promoting the progress of unmanned driving, AR and other popular applications. Closed-loop detection is a real-time method in VISLAM to check whether the trajectory of the moving object coincides with the previous location. It plays the role of correcting the cumulative error of the pose and map creation of the moving object in the process of moving forward. It is an essential and important part of VISLAM. . [0003] The closed-loop detection should have the characteristics of accuracy, high efficiency and real-time, and at the same time, it faces key problems such as the reasonable selection of key frames, the perceptual confusion of the image caused by repeated scenes, the selection of the clos...

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 Applications(China)
IPC IPC(8): G06K9/00G01C25/00
CPCG01C25/005G06V20/40G06V20/46
Inventor 芦佳振胡茂青韩松来董晶罗世彬
Owner CENT SOUTH UNIV
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products

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

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com