Laser-Based Online Sliding-Window Approach for UAV Loop-Closure Detection in Urban Environments

Abstract

Online loop-closure detection serves as an essential task for Unmanned Aerial Vehicles (UAVs) equipped with laser scanners. Due to the inherent errors in UAVs' pose estimation, a 3-D reconstruction algorithm is adopted to perform 3-D map building, which establishes probabilistic models of the system according to the assumption of errors. To meet the demand of online loop-closure detection using sequential 2-D laser data, a robust ISW-NDT (incremental sliding-window-based NDT) approach is proposed, which compares the appearance similarity between two scans by sliding a window with fixed size. Compared with the conventional 3-D NDT approach, the proposed loop-closure detection algorithm is capable of providing superior performance in large-scale outdoor environments, achieving higher recall rate at 100% precision and ensuring successful online implementation. Experimental results show the validity and robustness of the proposed method.