Nonlinear Observers Design for Vision-Aided Inertial Navigation Systems
This work provides a more robust and stable estimation solution for vision-aided inertial navigation systems, which is crucial for applications requiring precise and reliable state estimation.
This paper addresses the simultaneous estimation of attitude, position, and linear velocity for vision-aided inertial navigation systems. The authors propose a nonlinear observer that guarantees almost global asymptotic stability and local exponential stability, unlike existing local Kalman-type observers.
This paper deals with the simultaneous estimation of the attitude, position and linear velocity for vision-aided inertial navigation systems. We propose a nonlinear observer on $SO(3)\times \mathbb{R}^{15}$ relying on body-frame acceleration, angular velocity and (stereo or monocular) bearing measurements of some landmarks that are constant and known in the inertial frame. Unlike the existing local Kalman-type observers, our proposed nonlinear observer guarantees almost global asymptotic stability and local exponential stability. A detailed uniform observability analysis has been conducted and sufficient conditions are derived. Moreover, a hybrid version of the proposed observer is provided to handle the intermittent nature of the measurements in practical applications. Simulation and experimental results are provided to illustrate the effectiveness of the proposed state observer.