Finite Memory-Simultaneous Localization and Calibration With Application to Mobile Robots

被引：0

作者：

Lee, Dong Kyu ^{[1
]}

Pak, Jung Min ^{[2
]}

Shi, Peng ^{[3
,4
]}

Ahn, Choon Ki ^{[1
]}

机构：

[1] Korea Univ, Sch Elect Engn, Seoul 13391, South Korea

[2] Korea Natl Univ Transportat, Dept Artificial Intelligence, Uiwang 16106, South Korea

[3] Univ Adelaide, Sch Elect & Mech Engn, Adelaide, SA 5005, Australia

[4] Obuda Univ, Res & Innovat Ctr, H-1034 Budapest, Hungary

来源：

IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS | 2024年

基金：

新加坡国家研究基金会;

关键词：

Control input error; finite memory- simultaneous localization and calibration (FM-SLAC); mobile robot; simultaneous localization and calibration (SLAC); ODOMETRY; STATE; KALMAN;

D O I：

10.1109/TIE.2024.3485709

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

The movement of mobile robots can deviate from the control input due to factors such as wheel slip, drift, and unexpected motor loads, degrading the localization accuracy. To address this issue, a novel finite memory-simultaneous localization and calibration (FM-SLAC) is presented in this article. The proposed algorithm estimates any unknown component in the control input that is causing an error in the robot motion and then uses it to calibrate the localization results. The presented FM-SLAC has inherent robustness against modeling and computational errors due to its unique finite memory structure, allowing it to overcome the limitations of the existing algorithms. We conducted robot localization experiments in two scenarios where robot motion deviated from the control input to validate the performance of the proposed algorithm.

引用

页数：10

共 32 条

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