Convolutional Autoencoder aided loop closure detection for monocular SLAM

Original Loop-Closure Detection Algorithm for Monocular vSLAM

Vision-based simultaneous localization and mapping (vSLAM) is a well-established problem in mobile robotics and monocular vSLAM is one of the most challenging variations of that problem nowadays. In this work we study one of the core post-processing optimization mechanisms in vSLAM, e.g. loop-closure detection. We analyze the existing methods and propose original algorithm for loop-closure dete...

Robust Relocalization Based on Active Loop Closure for Real-Time Monocular SLAM

Unified Loop Closing and Recovery for Real Time Monocular SLAM

We present a unified method for recovering from tracking failure and closing loops in real time monocular simultaneous localisation and mapping. Within a graph-based map representation, we show that recovery and loop closing both reduce to the creation of a graph edge. We describe and implement a bag-of-words appearance model for ranking potential loop closures, and a robust method for using bo...

A comparison of loop closing techniques in monocular SLAM

Loop closure detection systems for monocular SLAM come in three broad categories: (i) map-to-map, (ii) image-to-image and (iii) image-to-map. In this paper, we have chosen an implementation of each and performed experiments allowing the three approaches to be compared. The sequences used include both indoor and outdoor environments and single and multiple loop trajectories. © 2009 Elsevier B.V....

An Active Visual Loop Closure Detection and Validation System for Topological SLAM

Loop closing is a vital component for mobile robot navigation without a priori information of the environment, since the mobile robot has to explore, build and at the same time maintain a globally consistent map. Moreover, it allows the mobile robot to recover from positional drifts due to errors associated with sensor measurements once loop closing is performed. In this paper, an active loop c...