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Pregled bibliografske jedinice broj: 884264

Human motion estimation on Lie groups using IMU measurements


Joukov, Vladimir; Ćesić, Josip; Westermann, Kevin; Marković, Ivan; Kulić, Dana; Petrović, Ivan
Human motion estimation on Lie groups using IMU measurements // Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2017)
Vancouver, Kanada, 2017. (predavanje, međunarodna recenzija, cjeloviti rad (in extenso), znanstveni)


Naslov
Human motion estimation on Lie groups using IMU measurements

Autori
Joukov, Vladimir ; Ćesić, Josip ; Westermann, Kevin ; Marković, Ivan ; Kulić, Dana ; Petrović, Ivan

Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni

Izvornik
Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2017) / - , 2017

Skup
IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2017)

Mjesto i datum
Vancouver, Kanada, 24.-29.09.2017.

Vrsta sudjelovanja
Predavanje

Vrsta recenzije
Međunarodna recenzija

Ključne riječi
Human motion estimation, Lie groups, IMU

Sažetak
This paper proposes a new algorithm for human motion estimation using inertial measurement unit (IMU) measurements. We model the joints by matrix Lie groups, namely the special orthogonal groups SO(2) and SO(3), representing rotations in 2D and 3D space, respectively. The state space is defined by the Cartesian product of the rotation groups and their velocities and accelerations, given a kinematic model of the articulated body. In order to estimate the state, we propose the Lie Group Extended Kalman Filter (LG-EKF), thus explicitly accounting for the non-Euclidean geometry of the state space, and we derive the LG-EKF recursion for articulated motion estimation based on IMU measurements. The performance of the proposed algorithm is compared to the EKF based on Euler angle parametrization in both simulation and real-world experiments. The results show that the proposed filter is a significant improvement over the Euler angles based EKF, since it estimates motion more accurately and is not affected by gimbal lock.

Izvorni jezik
Engleski

Znanstvena područja
Elektrotehnika, Računarstvo, Temeljne tehničke znanosti



POVEZANOST RADA


Ustanove
Fakultet elektrotehnike i računarstva, Zagreb