UKF-SLAM Implementation for the Optical Navigation System of a Lunar Lander

Abstract

This thesis project addresses the problem of state estimation in the context of the optical navigation system of an autonomous lunar lander. This work presents a state estimator based on the Unscented Kalman Filter and the Simultaneous Localization and Mapping algorithm. The proposed estimator complies with two requirements: use of a single camera to interface with the environment and accurate state estimation in absence of absolute position references, such as measurements of vehicle's position in world coordinates. In order to cope with the first constrain, the Inverse Depth Parametrization is introduced to model the 3D landmarks observed from the camera.