A constrained Extended Kalman Filter for dynamically consistent inverse kinematics and inertial parameters identification

V. Bonnet; G. Daune; V. Joukov; R. Dumas; P. Fraisse; D. Kulic; A. Seilles; S. Andary; G. Venture

doi:10.1109/BIOROB.2016.7523749

A constrained Extended Kalman Filter for dynamically consistent inverse kinematics and inertial parameters identification

V. Bonnet, G. Daune, V. Joukov, R. Dumas, P. Fraisse, D. Kulic, A. Seilles, S. Andary, G. Venture

Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Research

10 Citations (Scopus)

Abstract

This paper presents a method for the real-Time determination of joint angles, velocities, accelerations and joint torques of a human. The proposed method is based on a constrained Extended Kalman Filter that combines stereophotogrammetric and dynamometric data. In addition to the joint variables, subject-specific segment lengths and inertial parameters are identified. Constraints are added to the filter, by restricting the optimal Kalman gain, in order to obtain physically consistent parameters. An optimal tuning procedure of the filter's gains and a sensitivity analysis is presented. The method is validated in the plane on four human subjects and shows very good tracking of skin markers with a RMS difference lower than 15 mm. External ground reaction forces and resultant moment are also accurately estimated with an RMS difference below 3 N and 6 N.m, respectively.

Original language	English
Title of host publication	2016 6th IEEE International Conference on Biomedical Robotics and Biomechatronics (BioRob 2016)
Editors	A. Bezerianos, H.I. Krebs, S.L. Kukreja
Place of Publication	Piscataway NJ USA
Publisher	IEEE, Institute of Electrical and Electronics Engineers
Pages	944-949
Number of pages	6
ISBN (Electronic)	9781509032877
ISBN (Print)	9781509032884
DOIs	https://doi.org/10.1109/BIOROB.2016.7523749
Publication status	Published - 2016
Externally published	Yes
Event	International Conference on Biomedical Robotics and Biomechatronics 2016 - National University of Singapore, University Town, Singapore Duration: 26 Jun 2016 → 29 Jun 2016 Conference number: 6th https://ieeexplore-ieee-org.ezproxy.lib.monash.edu.au/xpl/conhome/7518174/proceeding (Proceedings)

Conference

Conference	International Conference on Biomedical Robotics and Biomechatronics 2016
Abbreviated title	BioRob 2016
Country/Territory	Singapore
City	University Town
Period	26/06/16 → 29/06/16
Internet address	https://ieeexplore-ieee-org.ezproxy.lib.monash.edu.au/xpl/conhome/7518174/proceeding (Proceedings)

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10.1109/BIOROB.2016.7523749

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Bonnet, V., Daune, G., Joukov, V., Dumas, R., Fraisse, P., Kulic, D., Seilles, A., Andary, S., & Venture, G. (2016). A constrained Extended Kalman Filter for dynamically consistent inverse kinematics and inertial parameters identification. In A. Bezerianos, H. I. Krebs, & S. L. Kukreja (Eds.), 2016 6th IEEE International Conference on Biomedical Robotics and Biomechatronics (BioRob 2016) (pp. 944-949). IEEE, Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/BIOROB.2016.7523749

Bonnet, V. ; Daune, G. ; Joukov, V. et al. / A constrained Extended Kalman Filter for dynamically consistent inverse kinematics and inertial parameters identification. 2016 6th IEEE International Conference on Biomedical Robotics and Biomechatronics (BioRob 2016). editor / A. Bezerianos ; H.I. Krebs ; S.L. Kukreja. Piscataway NJ USA : IEEE, Institute of Electrical and Electronics Engineers, 2016. pp. 944-949

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title = "A constrained Extended Kalman Filter for dynamically consistent inverse kinematics and inertial parameters identification",

abstract = "This paper presents a method for the real-Time determination of joint angles, velocities, accelerations and joint torques of a human. The proposed method is based on a constrained Extended Kalman Filter that combines stereophotogrammetric and dynamometric data. In addition to the joint variables, subject-specific segment lengths and inertial parameters are identified. Constraints are added to the filter, by restricting the optimal Kalman gain, in order to obtain physically consistent parameters. An optimal tuning procedure of the filter's gains and a sensitivity analysis is presented. The method is validated in the plane on four human subjects and shows very good tracking of skin markers with a RMS difference lower than 15 mm. External ground reaction forces and resultant moment are also accurately estimated with an RMS difference below 3 N and 6 N.m, respectively.",

author = "V. Bonnet and G. Daune and V. Joukov and R. Dumas and P. Fraisse and D. Kulic and A. Seilles and S. Andary and G. Venture",

year = "2016",

doi = "10.1109/BIOROB.2016.7523749",

language = "English",

isbn = "9781509032884",

pages = "944--949",

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booktitle = "2016 6th IEEE International Conference on Biomedical Robotics and Biomechatronics (BioRob 2016)",

publisher = "IEEE, Institute of Electrical and Electronics Engineers",

address = "United States of America",

note = "International Conference on Biomedical Robotics and Biomechatronics 2016, BioRob 2016 ; Conference date: 26-06-2016 Through 29-06-2016",

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Bonnet, V, Daune, G, Joukov, V, Dumas, R, Fraisse, P, Kulic, D, Seilles, A, Andary, S & Venture, G 2016, A constrained Extended Kalman Filter for dynamically consistent inverse kinematics and inertial parameters identification. in A Bezerianos, HI Krebs & SL Kukreja (eds), 2016 6th IEEE International Conference on Biomedical Robotics and Biomechatronics (BioRob 2016). IEEE, Institute of Electrical and Electronics Engineers, Piscataway NJ USA, pp. 944-949, International Conference on Biomedical Robotics and Biomechatronics 2016, University Town, Singapore, 26/06/16. https://doi.org/10.1109/BIOROB.2016.7523749

A constrained Extended Kalman Filter for dynamically consistent inverse kinematics and inertial parameters identification. / Bonnet, V.; Daune, G.; Joukov, V. et al.
2016 6th IEEE International Conference on Biomedical Robotics and Biomechatronics (BioRob 2016). ed. / A. Bezerianos; H.I. Krebs; S.L. Kukreja. Piscataway NJ USA: IEEE, Institute of Electrical and Electronics Engineers, 2016. p. 944-949.

Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Research

TY - GEN

T1 - A constrained Extended Kalman Filter for dynamically consistent inverse kinematics and inertial parameters identification

AU - Bonnet, V.

AU - Daune, G.

AU - Joukov, V.

AU - Dumas, R.

AU - Fraisse, P.

AU - Kulic, D.

AU - Seilles, A.

AU - Andary, S.

AU - Venture, G.

N1 - Conference code: 6th

PY - 2016

Y1 - 2016

N2 - This paper presents a method for the real-Time determination of joint angles, velocities, accelerations and joint torques of a human. The proposed method is based on a constrained Extended Kalman Filter that combines stereophotogrammetric and dynamometric data. In addition to the joint variables, subject-specific segment lengths and inertial parameters are identified. Constraints are added to the filter, by restricting the optimal Kalman gain, in order to obtain physically consistent parameters. An optimal tuning procedure of the filter's gains and a sensitivity analysis is presented. The method is validated in the plane on four human subjects and shows very good tracking of skin markers with a RMS difference lower than 15 mm. External ground reaction forces and resultant moment are also accurately estimated with an RMS difference below 3 N and 6 N.m, respectively.

AB - This paper presents a method for the real-Time determination of joint angles, velocities, accelerations and joint torques of a human. The proposed method is based on a constrained Extended Kalman Filter that combines stereophotogrammetric and dynamometric data. In addition to the joint variables, subject-specific segment lengths and inertial parameters are identified. Constraints are added to the filter, by restricting the optimal Kalman gain, in order to obtain physically consistent parameters. An optimal tuning procedure of the filter's gains and a sensitivity analysis is presented. The method is validated in the plane on four human subjects and shows very good tracking of skin markers with a RMS difference lower than 15 mm. External ground reaction forces and resultant moment are also accurately estimated with an RMS difference below 3 N and 6 N.m, respectively.

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SN - 9781509032884

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BT - 2016 6th IEEE International Conference on Biomedical Robotics and Biomechatronics (BioRob 2016)

A2 - Bezerianos, A.

A2 - Krebs, H.I.

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PB - IEEE, Institute of Electrical and Electronics Engineers

CY - Piscataway NJ USA

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Y2 - 26 June 2016 through 29 June 2016

ER -

Bonnet V, Daune G, Joukov V, Dumas R, Fraisse P, Kulic D et al. A constrained Extended Kalman Filter for dynamically consistent inverse kinematics and inertial parameters identification. In Bezerianos A, Krebs HI, Kukreja SL, editors, 2016 6th IEEE International Conference on Biomedical Robotics and Biomechatronics (BioRob 2016). Piscataway NJ USA: IEEE, Institute of Electrical and Electronics Engineers. 2016. p. 944-949 doi: 10.1109/BIOROB.2016.7523749

A constrained Extended Kalman Filter for dynamically consistent inverse kinematics and inertial parameters identification

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