Proceedings of the 2nd International Conference on Computer Engineering, Information Science & Application Technology (ICCIA 2017)

Research on EKF-Based Localization Method of Tracked Mobile Robot

Authors
Junsuo Qu, Qipeng Zhang, Leichao Hou, Ruijun Zhang, Kaiming Ting
Corresponding Author
Junsuo Qu
Available Online July 2016.
DOI
10.2991/iccia-17.2017.98How to use a DOI?
Keywords
Mobile robot , position ,heading angle ,Extended Kalman Filtering , Odometry
Abstract

To estimate the position and heading angle of mobile robot precisely, an measurement variable estimation model was proposed to adapt any angle. Fusing the predictive value of odometry and measurement data of multiple sensors by the Extended Kalman Filtering (EKF) for reducing the accumulative error by using only traditional odometry. The proposed models is verified by Matlab simulation and experimental results.

Copyright
© 2017, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 2nd International Conference on Computer Engineering, Information Science & Application Technology (ICCIA 2017)
Series
Advances in Computer Science Research
Publication Date
July 2016
ISBN
978-94-6252-361-6
ISSN
2352-538X
DOI
10.2991/iccia-17.2017.98How to use a DOI?
Copyright
© 2017, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Junsuo Qu
AU  - Qipeng Zhang
AU  - Leichao Hou
AU  - Ruijun Zhang
AU  - Kaiming Ting
PY  - 2016/07
DA  - 2016/07
TI  - Research on EKF-Based Localization Method of Tracked Mobile Robot
BT  - Proceedings of the 2nd International Conference on Computer Engineering, Information Science & Application Technology (ICCIA 2017)
PB  - Atlantis Press
SP  - 582
EP  - 587
SN  - 2352-538X
UR  - https://doi.org/10.2991/iccia-17.2017.98
DO  - 10.2991/iccia-17.2017.98
ID  - Qu2016/07
ER  -