We present a novel system to object pose estimation by fusing vision and inertial data.
Different algorithms for fusing data from inertial sensors and monocular or stereo vision data are described and compared.
The system error propagation property is analyzed.
The performance of the proposed system is assessed by simulation and experimental data.
The system can achieve accurate, fast and low-cost 6-DoF pose estimation.