Adaptive Monte-Carnot positioning method incorporating two-dimensional code information

A technology of two-dimensional code information and positioning method, applied in the field of Monte Carlo positioning, can solve the problems of unsatisfactory accuracy, complex design of artificial road signs, and low positioning accuracy

Active Publication Date: 2019-04-05
CHONGQING UNIV OF POSTS & TELECOMM
View PDF18 Cites 16 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, due to the complex design of artificial landmarks and the large amount of data required for the establishment of landmark databases, the positioning accuracy is low, which cannot meet the accuracy and requires a large amount of calculation.

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
  • Adaptive Monte-Carnot positioning method incorporating two-dimensional code information
  • Adaptive Monte-Carnot positioning method incorporating two-dimensional code information
  • Adaptive Monte-Carnot positioning method incorporating two-dimensional code information

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0040] The technical solutions in the embodiments of the present invention will be described clearly and in detail below with reference to the drawings in the embodiments of the present invention. The described embodiments are only some of the embodiments of the invention.

[0041] The technical scheme that the present invention solves the problems of the technologies described above is:

[0042] Such as figure 1 As shown, the present invention provides a kind of self-adaptive Monte Cano positioning method that incorporates two-dimensional code information, and it comprises the following steps:

[0043] S1, the sampling set at time χ t-1 , each particle corresponds to the estimated trajectory of the robot at this point, and the control amount u applied at time t-1 t and the global coordinate information x provided by the QR code c As input, the absolute position information provided by the QR code can correct the odometer motion model;

[0044] In the time interval (t-1,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 claims an adaptive Monte-Carnot positioning method incorporating two-dimensional code information. The method comprises the steps of: S1, establishing a motion model by using absolute position information provided by the two-dimensional code and a control amount u<t> of an odometer; S2, performing particle sampling according to the established motion model, and estimating an initialpose of a robot; S3, using a two-dimensional laser sensor for ranging to establish an observation model; S4, determining the importance weight of each particle and updating the weight; S5, adaptivelyadjusting the number of particles required for the next iteration according to the distribution of the particles in a state space; and S6, determining the position of the robot in the environment according to the distribution of the particles. The adaptive Monte-Carnot positioning method incorporating the two-dimensional code information can accurately position the robot in the environment and reduce the calculation amount.

Description

technical field [0001] The invention belongs to the field of mobile robot navigation, in particular to a Monte Carlo positioning method incorporating two-dimensional code information. Background technique [0002] On the premise that the environment map is known, the problem of determining the pose of the mobile robot in the environment according to the environment perception and its own motion is called the localization problem. The Monte Carlo localization (MCL) algorithm samples the motion model and evaluates the importance weight of each particle in combination with the observation model to obtain the posterior reliability distribution of the system state. Successfully applied in the field of mobile robots, it is suitable for both local positioning and global positioning problems. The odometer motion model integrates the information of the photoelectric encoder on the wheel, and then obtains the relative difference of the pose of the robot relative to the previous sampl...

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): G01C21/00G01C21/20
CPCG01C21/005G01C21/20
Inventor 胡章芳曾林全罗元张毅
Owner CHONGQING UNIV OF POSTS & TELECOMM
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