Loop closure detection helps simultaneous localization and mapping systems reduce map
and state uncertainty via recognizing previously visited places along the path of a mobile …

During simultaneous localization and mapping, the robot should build a map of its
surroundings and simultaneously estimate its pose in the generated map. However, a …

Traditional attempts for loop closure detection typically use hand-crafted features, relying on
geometric and visual information only, whereas more modern approaches tend to use …

Loop closure detection is a key module for visual simultaneous localization and mapping
(SLAM). Most previous methods for this module have not made full use of the information …

Loop closure detection plays a very important role in the mobile robot navigation field. It is
useful in achieving accurate navigation in complex environments and reducing the …

Loop closure detection (LCD) is a challenging task to judge whether the current position of
an intelligent robot returns to the previously visited position. Mainstream appearance-based …

Loop closure detection is essential in visual simultaneous localization and mapping systems
to recognize previously visited scenes, reducing pose and map estimates uncertainty …

Loop-closure detection plays an important role in visual simultaneous localisation and
mapping; it is an independent part of the visual odometer and can effectively reduce its …

An image can be described in terms of appearance frequency of visual words. This
representation is implemented in bag-of-visual-words (BoVW)-based loop closure detection …

Loop closure detection is an essential tool of Simultaneous Localization and Mapping
(SLAM) to minimize drift in its localization. Many state-of-the-art loop closure detection (LCD) …