Offline motion tracking of multi-link mechanisms using inertial sensor fusion and EKF-preconditioned FGO
Aderajew Tilahun, Jeronimo Cox, Tomonari Furukawa, Gamini Dissanayake
Abstract
This paper presents a novel strategy for offline estimation of the spatial motion of a multi-link mechanism using Inertial Measurement Unit (IMU) sensors. Accelerometers, gyroscopes and magnetometers are strategically mounted and modeled to maximize measurement accuracy through the past work of inertial sensor fusion. The core contribution of this paper is the development of the Factor Graph Optimization (FGO) Preconditioned by the Extended Kalman Filter (EKF), which is termed FGOPreEKF in this paper, and its integration with the inertial sensor fusion. Since the online EKF efficiently derives the initial guess using the same motion and sensor models, the FGO estimates the motion of a multi-link mechanism efficiently and accurately. The proposed approach was experimentally validated on a two-link system mounted on a fast-moving linear axis, demonstrating superior accuracy compared to standalone EKF or FGO. These results demonstrate the potential of this approach for estimating multi-link motion in more complex scenarios.
BibTeX
@inproceedings{iros2025_offlinemotiontra,
title = {Offline motion tracking of multi-link mechanisms using inertial sensor fusion and EKF-preconditioned FGO},
author = {Aderajew Tilahun and Jeronimo Cox and Tomonari Furukawa and Gamini Dissanayake},
booktitle = {IROS 2025},
year = {2025}
}