Pose estimation using line-based dynamic vision and inertial sensors

In this paper, an observer problem from a computer vision application is studied. Rigid body pose estimation using inertial sensors and a monocular camera is considered and it is shown how rotation estimation can be decoupled from position estimation. Orientation estimation is formulated as an observer problem with implicit output where the states evolve on SO(3). A careful observability study reveals interesting group theoretic structures tied to the underlying system structure. A locally convergent observer where the states evolve on SO(3) is proposed and numerical estimates of the domain of attraction is given. Further, it is shown that, given convergent orientation estimates, position estimation can be formulated as a linear implicit output problem. From an applications perspective, it is outlined how delayed low bandwidth visual observations and high badwidth rate gyro measurements can provide high bandwidth estimates. This is consistent with real-time constraints due to the complementary characteristics of the sensors which are fused in a multirate way.