SciELO - Scientific Electronic Library Online

 
vol.12 número3Placing Safety Stock in Logistic Networks under Guaranteed-Service Time Inventory Models: An Application to the Automotive IndustryTime Course Changes in pH, Electrical Conductivity and Heavy Metals (Pb, Cr) of Wastewater Using Moringa oleifera Lam. Seed and Alum, a Comparative Evaluation índice de autoresíndice de assuntospesquisa de artigos
Home Pagelista alfabética de periódicos  

Serviços Personalizados

Journal

Artigo

Indicadores

Links relacionados

  • Não possue artigos similaresSimilares em SciELO

Compartilhar


Journal of applied research and technology

versão On-line ISSN 2448-6736versão impressa ISSN 1665-6423

J. appl. res. technol vol.12 no.3 Ciudad de México Jun. 2014

 

SLAM-R Algorithm of Simultaneous Localization and Mapping Using RFID for Obstacle Location and Recognition

 

R. Lemus, S. Díaz, C. Gutiérrez, D. Rodríguez and F. Escobar

 

Group of Systems Engineering and Robotics, Instituto Tecnológico de Toluca, Metepec, Estado de México, México. ralego2005@gmail.com

 

ABSTRACT

This paper presents an algorithm of simultaneous localization and mapping (SLAM) with a scanning laser range finder and radiofrequency identification technology (RFID) to include landmarks of an object or place within a generated map. For the testing phase was used of simulation software Anykode's Marilou and was used to build a virtual mobile robot with the features of the Pionner 3-AT, including a Hokuyo URG-04X scanning laser range finder and an Innovations RFID ID-12 reader. Validation of results was carried out with the cycle closure process to obtain the average error of the navigation path, resulting on an error of less than 50mm.

Keywords: SLAM, Mobile Robot, RFID, Navigation, Simulation.

 

RESUMEN

Este artículo presenta un algoritmo de localización y mapeo simultáneos (SLAM) con telémetro láser y un identificador de radiofrecuencia (RFID), con el propósito de incluir la referencia de un objeto o lugar dentro del mapa generado. Para la experimentación se utilizó el software de simulación Anykode Marilou, mediante el cual se construyó un robot móvil virtual con las características del Pionner 3-DX, con un telémetro láser Hokuyo URG-04X y el lector RFID ID-12 de Innovations. La validación de los resultados se realizó con el proceso de cierre de ciclo, con el fin de obtener el error promedio del recorrido de navegación, logrando un error menor a los 50 mm.

 

DESCARGAR ARTÍCULO EN FORMATO PDF

 

References

[1] Durrant H. and Bailey T., "Simultaneous localization and mapping: Part I", IEEE Robotics & Automation. pp. 99-108, 2006.         [ Links ]

[2] Bailey T. and Durrant H., "Simultaneous localization and mapping: Part II", IEEE Robotics & Automation. pp. 108-117, 2006.         [ Links ]

[3] T. Bailey, et. al. "Consistency of the FastSLAM algorithm", IEEE Int. Conf. Robotics and Automation, 2006.         [ Links ]

[4] M. Montemerlo and S. Thrun. "Simultaneous localization and mapping with unknown data association using FastSLAM", IEEE International Conference on Robotics and Automation, 1985-1991, 2003.         [ Links ]

[5] S.B. Williams, "Efficient Solutions to Autonomous Mapping and Navigation Problems", PhD thesis, University of Sydney, Australian Centre for Field Robotics, 2001.         [ Links ]

[6] J. Folkesson and H.I. Christensen, "Graphical SLAM a selfcorrecting map", IEEE International Conference on Robotics and Automation, 791-798, 2004.         [ Links ]

[7] S. Thrun, et al. "A real-time algorithm for mobile robot mapping with applications to multi-robot and 3D mapping", International Conference on Robotics and Automation, 321-328, 2000.         [ Links ]

[8] M. Deans and M. Hebert. "Experimental comparison of techniques for localization and mapping using a bearing-only sensor", International Symposium on Experimental Robotics, 2000.         [ Links ]

[9] G. Grisetti, et. al., "Improved Techniques for Grid Mapping with Rao-Blackwellized Particle Filters", IEEE Transactions and Robotics, 2006.         [ Links ]

[10] Guivant and E. Nebot, "Optimization of the Simultaneus Localization and Map Building for Real Time Implementation", IEEE Transactions on Robotics and Automation, 2001.         [ Links ]

[11] E. Nazar and R. Parr., "DP-SLAM: Fast, Robust, Simultaneus Localization and Mapping without Predetermined Landmarks", IJCAI, 2003.         [ Links ]

[12] Civera, O.G. Grasa, A.J. Davison and J.M.M. Montiel, "1-Point RANSAC for EKF Filtering. Application to Real-Time Structure from Motion and Visual Odometry", Journal of Field Robotics, 2010.         [ Links ]

[13] O. El Hamzaoui and B. Steux, "SLAM Algorithm with Parallel Localization Loops: TinySLAM 1.1", Automation and Logistics (ICAL), 2011.         [ Links ]

[14] M. Young, "The Technical Writer's Handbook", Mill Valley, CA: University Science, 1989.         [ Links ]

[15] Adams M. "Sensor modelling, design and data processing for autonomous navigation", World Scientific Series in Robotics and Intelligent Systems, 1999.         [ Links ]

[16] Borenstein J. and Feng L. "Correction of systematic odometry errors in mobile robots", IEEE/RSJ International Conference 1995, 569-574.         [ Links ]

[17] David M. et. al., "Using Laser Range Data for 3D SLAM in Outdoor Environments. Intelligent Robots and Systems", 2003, 188-193, October 2003.         [ Links ]

[18] Dissanayake M.W.M.G., et al. "A solution to the simultaneous localization and map building (slam) problem", Robotics and Automation, IEEE Transactions on 2001, 17(3):229-241.         [ Links ]

[19] Cyber Robotics, "Webots 6", Consulta 2012. http://cyberbotics.com.         [ Links ]

[20] The University Western Australia. "EyeSim Simulator", Consulta 2012. http://robotics.ee.uwa.edu.au/eyebot/doc/sim/sim.html.         [ Links ]

[21] The University Western Australia. "MOBS - Mobile Robot Simulator", Consulta 2012. http://robotics.ee.uwa.edu.au/mobs/.         [ Links ] Anykode, "Marilou", Consulta 2012. http://anykode.com/mariloukeyfeatures.php        [ Links ]

Creative Commons License Todo o conteúdo deste periódico, exceto onde está identificado, está licenciado sob uma Licença Creative Commons