Item


Vertical edge-based mapping using range-augmented omnidirectional vision sensor

Laser range finder and omnidirectional cameras are becoming a promising combination of sensors to extract rich environmental information. This information includes textured plane extraction, vanishing points, catadioptric projection of vertical and horizontal lines, or invariant image features. However, many indoor scenes do not have enough texture information to describe the environment. In these situations, vertical edges could be used instead. This study presents a sensor model that is able to extract three-dimensional position of vertical edges from a range-augmented omnidirectional vision sensor. Using the unified spherical model for central catadioptric sensors and the proposed sensor model, the vertical edges are locally projected, improving the data association for mapping and localisation. The proposed sensor model was tested using the FastSLAM algorithm to solve the simultaneous localisation and mapping problem in indoor environments. Real-world qualitative and quantitative experiments are presented to validate the proposed approach using a Pioneer-3DX mobile robot equipped with a URG-04LX laser range finder and an omnidirectional camera with parabolic mirror

This work has been partially supported by the project RAIMON - Autonomous Underwater Robot for Marine Fish Farms Inspection and Monitoring (Ref. CTM2011-29691-C02-02)funded by the Spanish Ministry of Science and Innovation, the LASPAU-COLCIENCIAS grant no. 136-2008, the University of Valle contract no. 644-19-04-95, and the consolidated research group’s grant no. SGR2009-00380

© IET Computer Vision, 2013, Vol. 7, núm. 2, pp. 135-143

Institution of Engineering and Technology (IET)

Author: Bacca Cortés, Eval Bladimir
Cufí i Solé, Xavier
Salvi, Joaquim
Date: 2013
Abstract: Laser range finder and omnidirectional cameras are becoming a promising combination of sensors to extract rich environmental information. This information includes textured plane extraction, vanishing points, catadioptric projection of vertical and horizontal lines, or invariant image features. However, many indoor scenes do not have enough texture information to describe the environment. In these situations, vertical edges could be used instead. This study presents a sensor model that is able to extract three-dimensional position of vertical edges from a range-augmented omnidirectional vision sensor. Using the unified spherical model for central catadioptric sensors and the proposed sensor model, the vertical edges are locally projected, improving the data association for mapping and localisation. The proposed sensor model was tested using the FastSLAM algorithm to solve the simultaneous localisation and mapping problem in indoor environments. Real-world qualitative and quantitative experiments are presented to validate the proposed approach using a Pioneer-3DX mobile robot equipped with a URG-04LX laser range finder and an omnidirectional camera with parabolic mirror
This work has been partially supported by the project RAIMON - Autonomous Underwater Robot for Marine Fish Farms Inspection and Monitoring (Ref. CTM2011-29691-C02-02)funded by the Spanish Ministry of Science and Innovation, the LASPAU-COLCIENCIAS grant no. 136-2008, the University of Valle contract no. 644-19-04-95, and the consolidated research group’s grant no. SGR2009-00380
Format: application/pdf
ISSN: 1751-9632 (versió paper)
1751-9640 (versió electrònica)
Document access: http://hdl.handle.net/10256/11543
Language: eng
Publisher: Institution of Engineering and Technology (IET)
Collection: AGAUR/2009-2014/2009 SGR-380
MICINN/PN 2012-2014/CTM2011-29691-C02-02
Reproducció digital del document publicat a: http://dx.doi.org/10.1049/iet-cvi.2011.0214
Articles publicats (D-ATC)
Is part of: © IET Computer Vision, 2013, Vol. 7, núm. 2, pp. 135-143
Rights: Tots els drets reservats
Subject: Visió per ordinador
Computer vision
Imatges -- Processament
Image processing
Algorismes computacionals
Computer algorithms
Title: Vertical edge-based mapping using range-augmented omnidirectional vision sensor
Type: info:eu-repo/semantics/article
Repository: DUGiDocs

Subjects

Authors