Naslov
Estimation and observability analysis of human motion on Lie groups

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

Izvornik
IEEE Transactions on Cybernetics (2168-2267) 50 (2020), 3; 1321-1332

Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni

Ključne riječi
Human Body Kinematics ; Motion Estimation on Lie Groups ; Marker Measurements ; IMUs ; Observability Analysis

Sažetak
This paper proposes a framework for human pose estimation from wearable sensors that relies on Lie group representation to model the geometry of human movement. Human body joints are modeled by matrix Lie groups, using special orthogonal groups SO(2) and SO(3) for joint pose and special Euclidean group SE(3) for base link pose representation. To estimate the human joint pose, velocity and acceleration, we develop the equations for employing the Extended Kalman Filter on Lie Groups (LG-EKF), to explicitly account for the non-Euclidean geometry of the state space. We present the observability analysis of an arbitrarily long kinematic chain of SO(3) elements based on a differential geometric approach, representing a generalization of kinematic chains of a human body. The observability is investigated for the system using marker position measurements. The proposed algorithm is compared to two competing approaches, the EKF and unscented KF (UKF) based on Euler angle parametrization, in both simulations and extensive real-world experiments. The results show that the proposed approach achieves significant improvements over the Euler angle based filters. It provides more accurate pose estimates, is not sensitive to gimbal lock, and more consistently estimates covariances.

Izvorni jezik
Engleski

Znanstvena područja
Elektrotehnika, Računarstvo, Temeljne tehničke znanosti

POVEZANOST RADA