Real-Time SLAM Based on Image Stitching for Autonomous Navigation of UAVs in GNSS-Denied Regions

This paper introduces a novel visual Simultaneous Localization and Mapping (SLAM) system, which is based on image stitching technique. It is proposed to determine the position of unmanned aerial vehicles (UAVs) in GNSS-denied regions. Image stitching technique is adopted to overcome the limitations of current methods in terms of complexity and memory requirement. Also, the proposed method provides a solution to localize UAVs in unknown paths and to cope with modifications of landmarks. To evaluate the proposed method, several experiments have been conducted targeting datasets of images captured by UAVs in different environments. The obtained results demonstrate the effectiveness of the proposed method.