LexToMap: lexical-based topological mapping

 

Authors
Rangel, José Carlos; Martínez Gómez, Jesus; García Varea, Ismael; Cazorla, Miguel
Format
Article
Status
publishedVersion
Description

Any robot should be provided with a proper representation of its environment in order to perform navigation and other tasks. In addition to metrical approaches, topological mapping generates graph representations in which nodes and edges correspond to locations and transitions. In this article, we present LexToMap, a topological mapping procedure that relies on image annotations. These annotations, represented in this work by lexical labels, are obtained from pre-trained deep learning models, namely CNNs, and are used to estimate image similarities. Moreover, the lexical labels contribute to the descriptive capabilities of the topological maps. The proposal has been evaluated using the KTH-IDOL 2 data-set, which consists of image sequences acquired within an indoor environment under three different lighting conditions. The generality of the procedure as well as the descriptive capabilities of the generated maps validate the proposal.
Any robot should be provided with a proper representation of its environment in order to perform navigation and other tasks. In addition to metrical approaches, topological mapping generates graph representations in which nodes and edges correspond to locations and transitions. In this article, we present LexToMap, a topological mapping procedure that relies on image annotations. These annotations, represented in this work by lexical labels, are obtained from pre-trained deep learning models, namely CNNs, and are used to estimate image similarities. Moreover, the lexical labels contribute to the descriptive capabilities of the topological maps. The proposal has been evaluated using the KTH-IDOL 2 data-set, which consists of image sequences acquired within an indoor environment under three different lighting conditions. The generality of the procedure as well as the descriptive capabilities of the generated maps validate the proposal.

Publication Year
2019
Language
eng
Topic
Topological mapping
deep learning
localization
image annotations
lexical labels
Topological mapping
deep learning
localization
image annotations
lexical labels
Repository
RI de Documento Digitales de Acceso Abierto de la UTP
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https://www.tandfonline.com/doi/abs/10.1080/01691864.2016.1261045
https://ridda2.utp.ac.pa/handle/123456789/9434
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