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

SLAM method based on RGB-D image

A RGB-D, image technology, applied in the direction of instruments, biological neural network models, character and pattern recognition, etc., can solve the problems of serious time-consuming, large matching range, unreasonable accuracy and real-time performance

Active Publication Date: 2021-03-26
CHANGAN UNIV
View PDF8 Cites 2 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, there are still some problems in the above method: first, using violent matching to match feature points requires each feature to be matched with all other features, the matching range is large, and time-consuming is serious; second, the accuracy and real-time performance are not rational

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
  • SLAM method based on RGB-D image

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0090] Such as figure 1 Shown a kind of SLAM method based on RGB-D image, this method comprises the following steps:

[0091] Step 1. Acquisition of RGB-D images:

[0092] Use the depth camera to collect the space to be shot in real time according to the preset collection time, and send the RGB-D images collected at each sampling time to the computer; where the RGB-D image collected at the i-th sampling time includes the first The i-frame color image and the depth value corresponding to the i-th frame color image, i is a positive integer, and 1≤i≤M, M represents the total number of frames of the color image;

[0093] Step 2, feature point extraction and matching of RGB-D image:

[0094] Step 201, the computer adopts the ORB algorithm to extract the feature points of the i-th color image to obtain the feature point description subset of the i-th color image; wherein, the feature point descriptor corresponding to the a-th feature point in the i-th color image Denote as the at...

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 an SLAM method based on an RGB-D image. The method comprises the following steps: 1, acquiring the RGBD image; 2, extracting and matching feature points of the RGB-D image; 3,calculating a rotation matrix and a translation matrix; 4, acquiring a key frame in the RGBD image; 5, performing closed-loop judgment on the key frame; 6, carrying out global optimization on the RGB-D image; and 7, constructing a grid map. The method is simple in step, reasonable in design and convenient to implement, the violent matching problem is solved, errors, caused by mass difference of matching points, of the pose of the depth camera are reduced, the precision and real-time performance of SLAM are improved, and therefore the requirement for real-time SLAM of a robot can be met, and extremely high precision is achieved.

Description

technical field [0001] The invention belongs to the technical field of grid map construction, and in particular relates to a SLAM method based on RGB-D images. Background technique [0002] With the continuous development of intelligent robot technology, researchers hope that one day robots can observe and understand the surrounding world through eyes, complete their own positioning and model the surrounding environment like humans. This problem is generally called Simultaneous Localization and Mapping (SLAM). VSLAM refers to the completion of real-time positioning and map construction through visual sensors. Integrating a visual sensor and an infrared sensor and achieving good synchronization between the information of the two sensors constitutes an RGB-D sensor. VSLAM based on RGB-D sensors is called RGB-D SLAM. The current SLAM methods mainly use SIFT feature point extraction for RGB-D images, and then use the nearest iterative point ICP algorithm to solve the optimal ...

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): G06K9/00G06K9/46G06K9/62G06N3/04
CPCG06N3/049G06V20/10G06V10/44G06N3/044G06F18/22
Inventor 荆树旭卢鹏宇柳有权翟晓惠刘佳玲
Owner CHANGAN 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