A unified approach of observability analysis for airborne SLAM

Abstract

An unmanned aerial vehicle (UAV) is arranged to explore an unknown environment and to map the features it finds when GPS is denied. It navigates using a statistical estimation technique known as simultaneous localization and mapping (SLAM) which allows for the simultaneous estimation of the location of the UAV as well as the location of the features it sees. Observability is a key aspect of the state estimation problem of SLAM. However, the dimension and variables of SLAM system might be changed with new features. To solve this issue, a unified approach of observability analysis for SLAM system is provided, through reorganizing the system model. The dimension and variables of SLAM system keep steady, then the PWCS theory can be used to analyze the local or total observability, and under special maneuver, some system states, such as the yaw angle, become observable. Simulation results validate the proposed method.

Keywords

unmanned aerial vehicle (UAV) / simultaneous localization and mapping (SLAM) / inertial navigation system (INS) / observability / extend Kalman filter (EKF)

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