Solving Short-Term Relocalization Problems In Monocular Keyframe Visual SLAM Using Spatial And Semantic Data

Abstract-- In Monocular Keyframe Visual Simultaneous Localization and Mapping (MKVSLAM) frameworks, when incremental position tracking fails, global pose has to be recovered in a short-time window, also known as short-term relocalization. This capability is crucial for mobile robots to have reliable navigation, build accurate maps, and have precise behaviors around human collaborators. This paper focuses on the development of robust short-term relocalization capabilities for mobile robots using a monocular camera system. A novel multimodal keyframe descriptor is introduced, that contains semantic information of objects detected in the environment and the spatial information of the camera. High level system overview: For each keyframe (colored Keyframe-based Place Recognition (KPR) method is proposed rectangles) the proposed multimodal descriptor is formed using that is formulated as a multi-stage keyframe filtering algorithm, semantic and spatial data. When tracking is lost in the red keyframe, leading to a new relocalization pipeline for MKVSLAM systems.