Loading…

An Optimization-Based UWB-IMU Fusion Framework for UGV

UWB and IMU fusion positioning methods have been widely concerned for its high accuracy and robustness in GNSS-denied environment. However, most of the existing methods are stay under the Markov assumption and ignore the credible estimation of the yaw angle. In this paper, we propose a novel tightly...

Full description

Saved in:
Bibliographic Details
Published in:IEEE sensors journal 2022-03, Vol.22 (5), p.4369-4377
Main Authors: Zheng, Shuaikang, Li, Zhitian, Liu, Yunfei, Zhang, Haifeng, Zou, Xudong
Format: Article
Language:English
Subjects:
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
cited_by cdi_FETCH-LOGICAL-c293t-a37663d9d2e1eda4d41d0c089c0a9b8fc68abc568ee158f6ca13d1b1c2f577933
cites cdi_FETCH-LOGICAL-c293t-a37663d9d2e1eda4d41d0c089c0a9b8fc68abc568ee158f6ca13d1b1c2f577933
container_end_page 4377
container_issue 5
container_start_page 4369
container_title IEEE sensors journal
container_volume 22
creator Zheng, Shuaikang
Li, Zhitian
Liu, Yunfei
Zhang, Haifeng
Zou, Xudong
description UWB and IMU fusion positioning methods have been widely concerned for its high accuracy and robustness in GNSS-denied environment. However, most of the existing methods are stay under the Markov assumption and ignore the credible estimation of the yaw angle. In this paper, we propose a novel tightly-coupled IMU and multiple UWB tags fusion framework based on a graph optimization model that is able to provide high precision positioning and attitude determination service, which provides a new technical approach for the practical application of UWB and IMU fusion. A relative rotation and motion state initialization algorithm is designed and presented, which solves the problems that IMU installation direction is difficult to measure and the initial state is not stationary in practical application. Simulation experiments shows the impact of UWB tags distribution distance and IMU noise parameters on system performance, which provides design reference for practical applications. Finally, the real-site experiment proves the positioning RMSE of 4 cm based on our fusion solution and these simulation evidences, which confirms the great performance of our fusion solution.
doi_str_mv 10.1109/JSEN.2022.3144660
format article
fullrecord <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_journals_2635044977</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><ieee_id>9686716</ieee_id><sourcerecordid>2635044977</sourcerecordid><originalsourceid>FETCH-LOGICAL-c293t-a37663d9d2e1eda4d41d0c089c0a9b8fc68abc568ee158f6ca13d1b1c2f577933</originalsourceid><addsrcrecordid>eNo9kE1LAzEQhoMoWKs_QLwseN6ayXeObWlrpdqDrnoLaZKFrbZbky2iv95dWjzNy_C8M_AgdA14AID13cPz5GlAMCEDCowJgU9QDzhXOUimTrtMcc6ofD9HFymtMQYtuewhMdxmy11Tbapf21T1Nh_ZFHxWvI3y-WORTfepXWbTaDfhu44fWVnHrJi9XqKz0n6mcHWcfVRMJy_j-3yxnM3Hw0XuiKZNbqkUgnrtSYDgLfMMPHZYaYetXqnSCWVXjgsVAnBVCmeBeliBIyWXUlPaR7eHu7tYf-1Dasy63sdt-9IQQTlmTEvZUnCgXKxTiqE0u1htbPwxgE2nx3R6TKfHHPW0nZtDpwoh_PNaKCFB0D8Mul8a</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2635044977</pqid></control><display><type>article</type><title>An Optimization-Based UWB-IMU Fusion Framework for UGV</title><source>IEEE Electronic Library (IEL) Journals</source><creator>Zheng, Shuaikang ; Li, Zhitian ; Liu, Yunfei ; Zhang, Haifeng ; Zou, Xudong</creator><creatorcontrib>Zheng, Shuaikang ; Li, Zhitian ; Liu, Yunfei ; Zhang, Haifeng ; Zou, Xudong</creatorcontrib><description>UWB and IMU fusion positioning methods have been widely concerned for its high accuracy and robustness in GNSS-denied environment. However, most of the existing methods are stay under the Markov assumption and ignore the credible estimation of the yaw angle. In this paper, we propose a novel tightly-coupled IMU and multiple UWB tags fusion framework based on a graph optimization model that is able to provide high precision positioning and attitude determination service, which provides a new technical approach for the practical application of UWB and IMU fusion. A relative rotation and motion state initialization algorithm is designed and presented, which solves the problems that IMU installation direction is difficult to measure and the initial state is not stationary in practical application. Simulation experiments shows the impact of UWB tags distribution distance and IMU noise parameters on system performance, which provides design reference for practical applications. Finally, the real-site experiment proves the positioning RMSE of 4 cm based on our fusion solution and these simulation evidences, which confirms the great performance of our fusion solution.</description><identifier>ISSN: 1530-437X</identifier><identifier>EISSN: 1558-1748</identifier><identifier>DOI: 10.1109/JSEN.2022.3144660</identifier><identifier>CODEN: ISJEAZ</identifier><language>eng</language><publisher>New York: IEEE</publisher><subject>Algorithms ; Distance measurement ; fusion positioning ; graph optimization ; IMU ; Optimization ; Position measurement ; Real-time systems ; Sensor fusion ; Sensors ; Tags ; UWB ; Velocity measurement ; Yaw</subject><ispartof>IEEE sensors journal, 2022-03, Vol.22 (5), p.4369-4377</ispartof><rights>Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2022</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c293t-a37663d9d2e1eda4d41d0c089c0a9b8fc68abc568ee158f6ca13d1b1c2f577933</citedby><cites>FETCH-LOGICAL-c293t-a37663d9d2e1eda4d41d0c089c0a9b8fc68abc568ee158f6ca13d1b1c2f577933</cites><orcidid>0000-0002-1346-4870 ; 0000-0003-2077-9253</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/9686716$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>314,780,784,27922,27923,54794</link.rule.ids></links><search><creatorcontrib>Zheng, Shuaikang</creatorcontrib><creatorcontrib>Li, Zhitian</creatorcontrib><creatorcontrib>Liu, Yunfei</creatorcontrib><creatorcontrib>Zhang, Haifeng</creatorcontrib><creatorcontrib>Zou, Xudong</creatorcontrib><title>An Optimization-Based UWB-IMU Fusion Framework for UGV</title><title>IEEE sensors journal</title><addtitle>JSEN</addtitle><description>UWB and IMU fusion positioning methods have been widely concerned for its high accuracy and robustness in GNSS-denied environment. However, most of the existing methods are stay under the Markov assumption and ignore the credible estimation of the yaw angle. In this paper, we propose a novel tightly-coupled IMU and multiple UWB tags fusion framework based on a graph optimization model that is able to provide high precision positioning and attitude determination service, which provides a new technical approach for the practical application of UWB and IMU fusion. A relative rotation and motion state initialization algorithm is designed and presented, which solves the problems that IMU installation direction is difficult to measure and the initial state is not stationary in practical application. Simulation experiments shows the impact of UWB tags distribution distance and IMU noise parameters on system performance, which provides design reference for practical applications. Finally, the real-site experiment proves the positioning RMSE of 4 cm based on our fusion solution and these simulation evidences, which confirms the great performance of our fusion solution.</description><subject>Algorithms</subject><subject>Distance measurement</subject><subject>fusion positioning</subject><subject>graph optimization</subject><subject>IMU</subject><subject>Optimization</subject><subject>Position measurement</subject><subject>Real-time systems</subject><subject>Sensor fusion</subject><subject>Sensors</subject><subject>Tags</subject><subject>UWB</subject><subject>Velocity measurement</subject><subject>Yaw</subject><issn>1530-437X</issn><issn>1558-1748</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><recordid>eNo9kE1LAzEQhoMoWKs_QLwseN6ayXeObWlrpdqDrnoLaZKFrbZbky2iv95dWjzNy_C8M_AgdA14AID13cPz5GlAMCEDCowJgU9QDzhXOUimTrtMcc6ofD9HFymtMQYtuewhMdxmy11Tbapf21T1Nh_ZFHxWvI3y-WORTfepXWbTaDfhu44fWVnHrJi9XqKz0n6mcHWcfVRMJy_j-3yxnM3Hw0XuiKZNbqkUgnrtSYDgLfMMPHZYaYetXqnSCWVXjgsVAnBVCmeBeliBIyWXUlPaR7eHu7tYf-1Dasy63sdt-9IQQTlmTEvZUnCgXKxTiqE0u1htbPwxgE2nx3R6TKfHHPW0nZtDpwoh_PNaKCFB0D8Mul8a</recordid><startdate>20220301</startdate><enddate>20220301</enddate><creator>Zheng, Shuaikang</creator><creator>Li, Zhitian</creator><creator>Liu, Yunfei</creator><creator>Zhang, Haifeng</creator><creator>Zou, Xudong</creator><general>IEEE</general><general>The Institute of Electrical and Electronics Engineers, Inc. (IEEE)</general><scope>97E</scope><scope>RIA</scope><scope>RIE</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7SP</scope><scope>7U5</scope><scope>8FD</scope><scope>L7M</scope><orcidid>https://orcid.org/0000-0002-1346-4870</orcidid><orcidid>https://orcid.org/0000-0003-2077-9253</orcidid></search><sort><creationdate>20220301</creationdate><title>An Optimization-Based UWB-IMU Fusion Framework for UGV</title><author>Zheng, Shuaikang ; Li, Zhitian ; Liu, Yunfei ; Zhang, Haifeng ; Zou, Xudong</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c293t-a37663d9d2e1eda4d41d0c089c0a9b8fc68abc568ee158f6ca13d1b1c2f577933</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2022</creationdate><topic>Algorithms</topic><topic>Distance measurement</topic><topic>fusion positioning</topic><topic>graph optimization</topic><topic>IMU</topic><topic>Optimization</topic><topic>Position measurement</topic><topic>Real-time systems</topic><topic>Sensor fusion</topic><topic>Sensors</topic><topic>Tags</topic><topic>UWB</topic><topic>Velocity measurement</topic><topic>Yaw</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Zheng, Shuaikang</creatorcontrib><creatorcontrib>Li, Zhitian</creatorcontrib><creatorcontrib>Liu, Yunfei</creatorcontrib><creatorcontrib>Zhang, Haifeng</creatorcontrib><creatorcontrib>Zou, Xudong</creatorcontrib><collection>IEEE All-Society Periodicals Package (ASPP) 2005-present</collection><collection>IEEE All-Society Periodicals Package (ASPP) 1998-Present</collection><collection>IEEE Xplore</collection><collection>CrossRef</collection><collection>Electronics &amp; Communications Abstracts</collection><collection>Solid State and Superconductivity Abstracts</collection><collection>Technology Research Database</collection><collection>Advanced Technologies Database with Aerospace</collection><jtitle>IEEE sensors journal</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Zheng, Shuaikang</au><au>Li, Zhitian</au><au>Liu, Yunfei</au><au>Zhang, Haifeng</au><au>Zou, Xudong</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>An Optimization-Based UWB-IMU Fusion Framework for UGV</atitle><jtitle>IEEE sensors journal</jtitle><stitle>JSEN</stitle><date>2022-03-01</date><risdate>2022</risdate><volume>22</volume><issue>5</issue><spage>4369</spage><epage>4377</epage><pages>4369-4377</pages><issn>1530-437X</issn><eissn>1558-1748</eissn><coden>ISJEAZ</coden><abstract>UWB and IMU fusion positioning methods have been widely concerned for its high accuracy and robustness in GNSS-denied environment. However, most of the existing methods are stay under the Markov assumption and ignore the credible estimation of the yaw angle. In this paper, we propose a novel tightly-coupled IMU and multiple UWB tags fusion framework based on a graph optimization model that is able to provide high precision positioning and attitude determination service, which provides a new technical approach for the practical application of UWB and IMU fusion. A relative rotation and motion state initialization algorithm is designed and presented, which solves the problems that IMU installation direction is difficult to measure and the initial state is not stationary in practical application. Simulation experiments shows the impact of UWB tags distribution distance and IMU noise parameters on system performance, which provides design reference for practical applications. Finally, the real-site experiment proves the positioning RMSE of 4 cm based on our fusion solution and these simulation evidences, which confirms the great performance of our fusion solution.</abstract><cop>New York</cop><pub>IEEE</pub><doi>10.1109/JSEN.2022.3144660</doi><tpages>9</tpages><orcidid>https://orcid.org/0000-0002-1346-4870</orcidid><orcidid>https://orcid.org/0000-0003-2077-9253</orcidid></addata></record>
fulltext fulltext
identifier ISSN: 1530-437X
ispartof IEEE sensors journal, 2022-03, Vol.22 (5), p.4369-4377
issn 1530-437X
1558-1748
language eng
recordid cdi_proquest_journals_2635044977
source IEEE Electronic Library (IEL) Journals
subjects Algorithms
Distance measurement
fusion positioning
graph optimization
IMU
Optimization
Position measurement
Real-time systems
Sensor fusion
Sensors
Tags
UWB
Velocity measurement
Yaw
title An Optimization-Based UWB-IMU Fusion Framework for UGV
url http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-14T04%3A30%3A14IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=An%20Optimization-Based%20UWB-IMU%20Fusion%20Framework%20for%20UGV&rft.jtitle=IEEE%20sensors%20journal&rft.au=Zheng,%20Shuaikang&rft.date=2022-03-01&rft.volume=22&rft.issue=5&rft.spage=4369&rft.epage=4377&rft.pages=4369-4377&rft.issn=1530-437X&rft.eissn=1558-1748&rft.coden=ISJEAZ&rft_id=info:doi/10.1109/JSEN.2022.3144660&rft_dat=%3Cproquest_cross%3E2635044977%3C/proquest_cross%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-c293t-a37663d9d2e1eda4d41d0c089c0a9b8fc68abc568ee158f6ca13d1b1c2f577933%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_pqid=2635044977&rft_id=info:pmid/&rft_ieee_id=9686716&rfr_iscdi=true