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

Human body target tracking method based on progressive unscented Kalman filtering

An unscented Kalman and human target technology, applied in the field of mobile robots, can solve the problems of poor stability and low precision, achieve the effects of reducing linearization error, improving tracking accuracy, and ensuring computational complexity

Active Publication Date: 2018-10-19
ZHEJIANG UNIV OF TECH
View PDF3 Cites 6 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] In order to overcome the deficiencies of low accuracy and poor stability of the existing human target tracking method, the present invention provides a human target tracking method based on progressive unscented Kalman filter. Under the premise of ensuring computational complexity, the method can Considering the impact of linearization error on the system, effectively improving the tracking accuracy of human targets

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
  • Human body target tracking method based on progressive unscented Kalman filtering
  • Human body target tracking method based on progressive unscented Kalman filtering
  • Human body target tracking method based on progressive unscented Kalman filtering

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0020] The present invention will be further described below in conjunction with the accompanying drawings.

[0021] refer to Figure 1 ~ Figure 3 , a human target tracking method based on progressive unscented Kalman filter, by figure 1 As shown in , the following robot uses a laser sensor to detect the human target, and obtains the distance and angle between the service robot and the human target; figure 2 As shown, according to the measurement information returned by the laser sensor, the positional relationship between the robot and the human target in the global coordinates is obtained through coordinate conversion. The state space model of the follower system is shown in formula (1), and the sensor measurement model is shown in formula ( 2) as shown:

[0022]

[0023]

[0024]

[0025]

[0026] Among them, the state vector of the system is and are the positions of the human target on the x-axis and y-axis at time k, respectively, and is the vel...

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

A human body target tracking method based on progressive unscented Kalman filtering is used for solving the problem of decrease of the system tracking performance, caused by a too large linearizationerror, and progressively introduces current measurement information in the measurement updating process to reduce the linearization error in order to effectively improve the human body target trackingprecision. A determination condition is introduced in the measurement gradual proceeding process to further compensate the linearization error existing in the system. Compared with existing target tracking methods, the method in the invention fully considers the influences of the linearization error on the system, and improves the human body target tracking precision on the premise of ensuring the computational complexity.

Description

technical field [0001] The invention belongs to the field of mobile robots, in particular to a human body target tracking method for following a robot. Background technique [0002] With the increasing requirements of social production and life, the mobile robot industry has developed very rapidly and gradually penetrated into the fields of social services, medical health and resource detection. In an unknown and complex dynamic environment, realizing the identification and tracking of service objects is one of the main ways to improve the environmental adaptability of mobile robots, and it is also the premise and basis for completing complex specified tasks through human-computer cooperation. [0003] In order to realize the effective detection and tracking of human targets by mobile robots, it is necessary to design a stable and good performance human target tracking estimator. Considering the nonlinear filtering problem in the process of human target tracking, some commo...

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): G01C21/20G01S17/66
CPCG01C21/20G01S17/66
Inventor 俞立郑婷婷杨旭升赵礼艳
Owner ZHEJIANG UNIV OF TECH
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