Novel LiDAR-assisted UWB positioning compensation for indoor robot localization

被引：14

作者：

Feng, Jidong ^{[1
]}

Wang, Lei ^{[2
]}

Li, Jian ^{[2
]}

Xu, Yuan ^{[1
,3
]}

Bi, Shuhui ^{[1
]}

Shen, Tao ^{[1
]}

机构：

[1] Univ Jinan, Sch Elect Engn, Jinan 250022, Peoples R China

[2] HIT Robot Grp Co Ltd HRG Shandong, Intelligent Equipment Res Inst, Jinan 250000, Peoples R China

[3] Shandong Beiming Med Technol Co Ltd, Jinan 250000, Peoples R China

来源：

2021 INTERNATIONAL CONFERENCE ON ADVANCED MECHATRONIC SYSTEMS (ICAMECHS) | 2021年

基金：

国家重点研发计划;

关键词：

Indoor localization; ultra wide band; LiDAR; extended Kalman filter;

D O I：

10.1109/ICAMechS54019.2021.9661496

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

In order to improve the localization error of the traditional ultra wide band (UWB) localization method, a novel light detection and ranging (LiDAR)-assisted UWB positioning compensation for indoor robot localization will be designed in this work. In details, two extended Kalman filters (EKFs) are employed. One is for providing a UWB-based position which is fused from the distances from reference nodes of UWB (URNS) to the target robot. And the data fusion models for the two EKFs will be derived. The other one is used to estimate the UWB position error by using the difference between the UWB and LiDAR-based distances. The test results show that the LiDAR-assisted UWB positioning compensation is effective to reduce the UWB localization error.

引用

页码：215 / 219

页数：5

共 6 条

[1] On Sigma-Point Update of Cubature Kalman Filter for GNSS/INS Under GNSS-Challenged Environment [J].

Cui, Bingbo ;

Wei, Xinhua ;

Chen, Xiyuan ;

Li, Jinyang ;

Li, Lin .

IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, 2019, 68 (09) :8671-8682

[2] Trajectory Optimization for Target Localization With Bearing-Only Measurement [J].

He, Shaoming ;

Shin, Hyo-Sang ;

Tsourdos, Antonios .

IEEE TRANSACTIONS ON ROBOTICS, 2019, 35 (03) :653-668

[3] Improving Tightly LiDAR/Compass/Encoder-Integrated Mobile Robot Localization with Uncertain Sampling Period Utilizing EFIR Filter [J].

Xu, Yuan ;

Shmaliy, Yuriy S. ;

Ma, Wanfeng ;

Jiang, Xianwei ;

Shen, Tao ;

Bi, Shuhui ;

Guo, Hang .

MOBILE NETWORKS & APPLICATIONS, 2021, 26 (01) :440-448

[4] Robust and accurate UWB-based indoor robot localisation using integrated EKF/EFIR filtering [J].

Xu, Yuan ;

Shmaliy, Yuriy S. ;

Ahn, Choon Ki ;

Tian, Guohui ;

Chen, Xiyuan .

IET RADAR SONAR AND NAVIGATION, 2018, 12 (07) :750-756

[5] Trial-and-error or avoiding a guess? Initialization of the Kalman filter [J].

Zhao, Shunyi ;

Huang, Biao .

AUTOMATICA, 2020, 121

[6] Fast Kalman-Like Optimal Unbiased FIR Filtering With Applications [J].

Zhao, Shunyi ;

Shmaliy, Yuriy S. ;

Liu, Fei .

IEEE TRANSACTIONS ON SIGNAL PROCESSING, 2016, 64 (09) :2284-2297

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