CV-SLAM using ceiling boundary

This paper deals with simultaneous localization and mapping(SLAM) problem for a mobile robot that travels around the indoor environments. A single camera looking up the ceiling is used as the only sensor. Line features are extracted from the boundaries between the ceiling and walls and parameterized for SLAM update. Extended Kalman Filter(EKF) is used for simultaneously estimating the current robot pose and building a map with the line features. When the robot is kidnapped, Monte Carlo Localization(MCL) is used for finding the robot pose. To improve the localization performance, the resampling method is modified. The experiment is practiced in our indoor test bed and the proposed algorithms are proved by the experimental results.