Submap-Based Pose-Graph Visual SLAM: A Robust Visual Exploration and Localization System* The work in this paper is supported by the National Natural Science Foundation of China (61603103, 61673125), the Natural Science Foundation of Guangdong of China (2016A030310293), and the Major Scientific and Technological Special Project of Guangdong of China (2016B090910003)

Abstract

For VSLAM (Visual Simultaneous Localization and Mapping), localization is a challenging task, especially for some challenging situations: textureless frames, motion blur, etc. To build a robust exploration and localization system in a given space, a submap-based VSLAM system is proposed in this paper. Our system uses a submap back-end and a visual front-end. The main advantage of our system is its robustness with respect to tracking failure, a common problem in current VSLAM algorithms. The robustness of our system is compared with the state-of-the-art in terms of average tracking percentage. The precision of our system is also evaluated in terms of ATE (absolute trajectory error) RMSE (root mean square error) comparing the state-of-the-art. The ability of our system in solving the “kidnapped” problem is demonstrated. Our system can improve the robustness of visual localization in challenging situations.