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Implicit Observation Model for Vision Aided Inertial Navigation of Aerial Vehicles Using Single Camera Vector Observations

Future smaller and maneuverable aerial vehicles have a need of high levels of autonomy and independence. This gives rise to the necessity for integrated navigation systems that supply reliable and accurate navigation parameters (position, velocity and attitude) in small and cost effective manner. In this paper we propose a new solution that provides aiding information to Inertial Navigation from pure vision means. Using single video camera and with no a priori knowledge of the environment we show that, it is possible to constrain the Inertial Navigation position, velocity and attitude divergence while moving in vicinity of a map point. Novel observation model of implicit form is developed and used in the paper. It is shown that such an integrated navigation system has a need for further integration with the guidance and control measurements and the vehicle motion to achieve better navigation accuracy.

Aerial vehicles; Autonomous navigation; Inertial Navigation; Vision; Vector Observations; Observation model; Extended Kalman filter

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