Reference-Free Adaptive Attitude Determination Method Using Low-Cost MARG Sensors

Jian Ding; Jin Wu; Mingsen Deng; Ming Liu

doi:10.1007/978-3-030-34995-0_4

Reference-Free Adaptive Attitude Determination Method Using Low-Cost MARG Sensors

Jian Ding
, Jin Wu
, Mingsen Deng^*
, Ming Liu

^*Corresponding author for this work

Department of Computer Science and Engineering

Research output: Chapter in Book/Conference Proceeding/Report › Conference Paper published in a book › peer-review

Abstract

In this paper, an improved iterative method for attitude determination using microelectromechanical-system (MEMS) Magnetic, Angular Rate, and Gravity (MARG) sensors is proposed. The proposed complementary filter is motivated by several existing algorithms and it decreases the amount of variables for iteration which consequently lowers the convergence time. To enhance the adaptive ability i.e. the performance under external acceleration, of the proposed method, a novel scheme is designed, where the gravity estimation residual is utilized for adaptive tuning of the complementary gain. Experiments are carried out to demonstrate the advantages of the proposed method. The comparisons with representative methods show that the proposed method is more effective, not only in convergence speed, but in dynamic performance under harsh conditions as well.

Original language	English
Title of host publication	Computer Vision Systems - 12th International Conference, ICVS 2019, Proceedings
Editors	Dimitrios Tzovaras, Dimitrios Giakoumis, Markus Vincze, Antonis Argyros
Publisher	Springer
Pages	35-48
Number of pages	14
ISBN (Print)	9783030349943
DOIs	https://doi.org/10.1007/978-3-030-34995-0_4
Publication status	Published - 2019
Event	12th International Conference on Computer Vision Systems, ICVS 2019 - Thessaloniki, Greece Duration: 23 Sept 2019 → 25 Sept 2019

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	11754 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	12th International Conference on Computer Vision Systems, ICVS 2019
Country/Territory	Greece
City	Thessaloniki
Period	23/09/19 → 25/09/19

Bibliographical note

Publisher Copyright:
© 2019, Springer Nature Switzerland AG.

Keywords

Attitude determination
Complementary filter
Gradient Descent Algorithm
MARG sensors
MEMS sensors

Access to Document

10.1007/978-3-030-34995-0_4

Cite this

Ding, J., Wu, J., Deng, M., & Liu, M. (2019). Reference-Free Adaptive Attitude Determination Method Using Low-Cost MARG Sensors. In D. Tzovaras, D. Giakoumis, M. Vincze, & A. Argyros (Eds.), Computer Vision Systems - 12th International Conference, ICVS 2019, Proceedings (pp. 35-48). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11754 LNCS). Springer. https://doi.org/10.1007/978-3-030-34995-0_4

Ding, Jian ; Wu, Jin ; Deng, Mingsen et al. / Reference-Free Adaptive Attitude Determination Method Using Low-Cost MARG Sensors. Computer Vision Systems - 12th International Conference, ICVS 2019, Proceedings. editor / Dimitrios Tzovaras ; Dimitrios Giakoumis ; Markus Vincze ; Antonis Argyros. Springer, 2019. pp. 35-48 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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title = "Reference-Free Adaptive Attitude Determination Method Using Low-Cost MARG Sensors",

abstract = "In this paper, an improved iterative method for attitude determination using microelectromechanical-system (MEMS) Magnetic, Angular Rate, and Gravity (MARG) sensors is proposed. The proposed complementary filter is motivated by several existing algorithms and it decreases the amount of variables for iteration which consequently lowers the convergence time. To enhance the adaptive ability i.e. the performance under external acceleration, of the proposed method, a novel scheme is designed, where the gravity estimation residual is utilized for adaptive tuning of the complementary gain. Experiments are carried out to demonstrate the advantages of the proposed method. The comparisons with representative methods show that the proposed method is more effective, not only in convergence speed, but in dynamic performance under harsh conditions as well.",

keywords = "Attitude determination, Complementary filter, Gradient Descent Algorithm, MARG sensors, MEMS sensors",

author = "Jian Ding and Jin Wu and Mingsen Deng and Ming Liu",

note = "Publisher Copyright: {\textcopyright} 2019, Springer Nature Switzerland AG.; 12th International Conference on Computer Vision Systems, ICVS 2019 ; Conference date: 23-09-2019 Through 25-09-2019",

year = "2019",

doi = "10.1007/978-3-030-34995-0\_4",

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isbn = "9783030349943",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

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Ding, J, Wu, J, Deng, M & Liu, M 2019, Reference-Free Adaptive Attitude Determination Method Using Low-Cost MARG Sensors. in D Tzovaras, D Giakoumis, M Vincze & A Argyros (eds), Computer Vision Systems - 12th International Conference, ICVS 2019, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 11754 LNCS, Springer, pp. 35-48, 12th International Conference on Computer Vision Systems, ICVS 2019, Thessaloniki, Greece, 23/09/19. https://doi.org/10.1007/978-3-030-34995-0_4

Reference-Free Adaptive Attitude Determination Method Using Low-Cost MARG Sensors. / Ding, Jian; Wu, Jin; Deng, Mingsen et al.
Computer Vision Systems - 12th International Conference, ICVS 2019, Proceedings. ed. / Dimitrios Tzovaras; Dimitrios Giakoumis; Markus Vincze; Antonis Argyros. Springer, 2019. p. 35-48 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11754 LNCS).

Research output: Chapter in Book/Conference Proceeding/Report › Conference Paper published in a book › peer-review

TY - GEN

T1 - Reference-Free Adaptive Attitude Determination Method Using Low-Cost MARG Sensors

AU - Ding, Jian

AU - Wu, Jin

AU - Deng, Mingsen

AU - Liu, Ming

PY - 2019

Y1 - 2019

N2 - In this paper, an improved iterative method for attitude determination using microelectromechanical-system (MEMS) Magnetic, Angular Rate, and Gravity (MARG) sensors is proposed. The proposed complementary filter is motivated by several existing algorithms and it decreases the amount of variables for iteration which consequently lowers the convergence time. To enhance the adaptive ability i.e. the performance under external acceleration, of the proposed method, a novel scheme is designed, where the gravity estimation residual is utilized for adaptive tuning of the complementary gain. Experiments are carried out to demonstrate the advantages of the proposed method. The comparisons with representative methods show that the proposed method is more effective, not only in convergence speed, but in dynamic performance under harsh conditions as well.

AB - In this paper, an improved iterative method for attitude determination using microelectromechanical-system (MEMS) Magnetic, Angular Rate, and Gravity (MARG) sensors is proposed. The proposed complementary filter is motivated by several existing algorithms and it decreases the amount of variables for iteration which consequently lowers the convergence time. To enhance the adaptive ability i.e. the performance under external acceleration, of the proposed method, a novel scheme is designed, where the gravity estimation residual is utilized for adaptive tuning of the complementary gain. Experiments are carried out to demonstrate the advantages of the proposed method. The comparisons with representative methods show that the proposed method is more effective, not only in convergence speed, but in dynamic performance under harsh conditions as well.

KW - Attitude determination

KW - Complementary filter

KW - Gradient Descent Algorithm

KW - MARG sensors

KW - MEMS sensors

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DO - 10.1007/978-3-030-34995-0_4

M3 - Conference Paper published in a book

AN - SCOPUS:85077015407

SN - 9783030349943

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 35

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BT - Computer Vision Systems - 12th International Conference, ICVS 2019, Proceedings

A2 - Tzovaras, Dimitrios

A2 - Giakoumis, Dimitrios

A2 - Vincze, Markus

A2 - Argyros, Antonis

PB - Springer

T2 - 12th International Conference on Computer Vision Systems, ICVS 2019

Y2 - 23 September 2019 through 25 September 2019

ER -

Ding J, Wu J, Deng M, Liu M. Reference-Free Adaptive Attitude Determination Method Using Low-Cost MARG Sensors. In Tzovaras D, Giakoumis D, Vincze M, Argyros A, editors, Computer Vision Systems - 12th International Conference, ICVS 2019, Proceedings. Springer. 2019. p. 35-48. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-030-34995-0_4

Reference-Free Adaptive Attitude Determination Method Using Low-Cost MARG Sensors

Abstract

Publication series

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Bibliographical note

Keywords

Access to Document

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