Abstract-In robotics applications such as SLAM (Simultaneous Localization and Mapping), loop closure detection is an integral component required to build a consistent topological or metric map. This paper presents an appearance based loop closure detection mechanism titled 'IBuILD' (Incremental bag of BInary words for Appearance based Loop closure Detection). The presented approach focuses on an online, incremental formulation of binary vocabulary generation for loop closure detection. The proposed approach does not require a prior vocabulary learning phase and relies purely on the appearance of the scene for loop closure detection without the need of odometry or GPS estimates. The vocabulary generation process is based on feature tracking between consecutive images to incorporate pose invariance. In addition, this process is coupled with a simple likelihood function to generate the most suitable loop closure candidate and a temporal consistency constraint to filter out inconsistent loop closures. Evaluation on different publicly available outdoor urban and indoor datasets shows that the presented approach is capable of generating higher recall at 100% precision in comparison to the state of the art.
The IBuILD system REF further improves the binary bag-of-word recipe by designing an online incremental system without the need for prior feature training.
IBuILD: Incremental bag of Binary words for appearance based loop closure detection
2015 IEEE International Conference on Robotics and Automation (ICRA)
2015 IEEE International Conference on Robotics and Automation (ICRA)
Mathematics Computer Science