Vision-Based Heading and Lateral Deviation Estimation for Indoor Navigation of a Quadrotor

Abstract

ABSTRACT In this paper, an effective vanishing point detection method based on grid-based approach for navigation of micro aerial vehicles (MAVs) in indoor corridor environment is described. The automation and navigation of MAVs in GPS-denied indoor environments is still a challenging task. To navigate in indoor corridors, on-board camera sensor is used as a sole sensor for estimating both the vehicle position and heading. Finally, the lateral deviation and heading of an MAV from the centre towards the right or left of the corridor are computed using vanishing point coordinates between two successive frames. By exploiting geometrical constraints inside buildings, long-term stable heading information is extracted. It is shown that the proposed method effectively eliminates heading drift in indoor corridor environment and is real-time capable. The measured parameters can be used to control an MAV when it deviates from the desired path of navigation.