Fast relative sensor orientation estimation in the presence of real-world disturbances

Fast relative sensor orientation estimation in the presence of real-world disturbances

Remmerswaal, Evan (Student TU Delft)
Weygers, Ive (Katholieke Universiteit Leuven)
Smit, G. (TU Delft Medical Instruments & Bio-Inspired Technology)
Kok, M. (TU Delft Team Manon Kok)

2021

We present a novel approach to estimate the relative sensor orientation from inertial sensors placed on connected body segments. Drift in the relative orientation estimates obtained by integrating the gyroscope measurements is corrected solely by incorporating common information in the inertial sensor measurements due to the connection of the body segments. We solve the estimation problem using a complementary filtering implementation to reduce the computational complexity. We study its robustness under common real-world model violations, e.g., soft tissue artifacts and spikes in the acceleration signals due to impacts. The efficacy of the method is illustrated with numerical simulations and is compared to a multiplicative extended Kalman filter implementation, both with and without outlier rejection. In addition, a human experiment strengthened the simulation results under realistic sensor errors.

http://resolver.tudelft.nl/uuid:c9d631b3-b670-4bcd-8c28-12ee53d8af29

https://doi.org/10.23919/ECC54610.2021.9654849

IEEE

2022-07-03

978-1-6654-7945-5

Proceedings of the European Control Conference (ECC 2021)

2021 European Control Conference (ECC), 2021-06-29 → 2021-07-02, Virtual , Netherlands

Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.

Institutional Repository

conference paper

© 2021 Evan Remmerswaal, Ive Weygers, G. Smit, M. Kok