Abstract
Abstract This paper examines the state estimation problem for unmanned aerial vehicles when commonly used positioning systems such as the global positioning system or indoor motion capture systems are unavailable. The proposed method uses inertial sensor measurements along with scaled position measurements from an onboard computer vision system which implements visual simultaneous localization and mapping. A state transformation puts the system into a linear time-varying form which simplifies observability analysis and allows for an observer design with sufficient conditions for convergence. The proposed design is validated by simulation.
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