LSH for loop closing detection in underwater visual SLAM

Author

Bonin-Font, Francisco ; Negre Carrasco, Pep Lluis ; Burguera Burguera, Antoni ; Codina, Gabriel Oliver

Author_Institution

Syst., Robot. & Vision Group, Univ. of the Balearic Islands (UIB), Palma de Mallorca, Spain

fYear

2014

fDate

16-19 Sept. 2014

Firstpage

1

Lastpage

4

Abstract

Effectiveness in loop closing detection is crucial to increase accuracy in SLAM (Simultaneous Localization and Mapping) for mobile robots. The most representative approaches to visual loop closing detection are based on feature matching or BOW (Bag of Words), being slow and needing a lot of memory resources or a previously defined vocabulary, which complicates and delays the whole process. This paper present a new visual LSH (Locality Sensitive Hashing)-based approach for loop closure detection, where images are hashed to accelerate considerably the whole comparison process. The algorithm is applied in AUV (Autonomous Underwater Vehicles), in several aquatic scenarios, showing promising results and the validity of this proposal to be applied online.

Keywords

SLAM (robots); autonomous underwater vehicles; feature extraction; image matching; mobile robots; robot vision; AUV; BOW; Bag of Words; autonomous underwater vehicles; feature matching; image hashing; memory resources; mobile robots; simultaneous localization and mapping; underwater visual SLAM; visual LSH-based approach; visual locality sensitive hashing-based approach; visual loop closing detection; Feature extraction; Indexes; Robustness; Simultaneous localization and mapping; Vectors; Visualization;

fLanguage

English

Publisher

ieee

Conference_Titel

Emerging Technology and Factory Automation (ETFA), 2014 IEEE

Conference_Location

Barcelona

Type

conf

DOI

10.1109/ETFA.2014.7005245

Filename

7005245