Design and implementation of an artificial vision system using a slamming technique on a mobile robotic platform
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visión artificial, sistema de percepción, SLAM, software, LSD_SLAM
The SLAM is one of the algorithms that were born with the intention of being able to position the
robot in an unknown environment while navigating through it and using the above information from
its sensors to build a map of the environment in which it is located. . To achieve the mapping, several
investigations have used sensors of ultrasound type, LIDAR, even cameras using artificial vision. The
objective of this research is focused on applying a SLAM technique on a mobile robotic platform. To
achieve this objective, a study is made of different existing SLAM methodologies that could meet the
expectations resulting in the LSD-SLAM, which with a suitable camera is able to obtain a semi-dense
3D map of the environment in which it works. It also develops in ROS (Robot Operating System) defined
as operating system, which should be taken into account for future research thanks to its great features.
Once researched, selected and implemented, the programming of the system was started by means of
tools and libraries which have support, in terms of reliable documentation and previously programmed
for their use.
Keywords: Laptop, cooling, HUB-USB, Master Cooler.
E. Rúa, A. Barrera, y N. Moreno, “Aprendizaje interactivo de Termodinámica de fluidos apoyado en las tecnologías de la información y comunicación”, Respuestas, vol. 19, no. 2, pp. 41-50, 2014.Diseño e implementación de un sistema de visión artificial usando una técnica de mapeo y localización simultánea (SLAM) sobre una plataforma robótica móvil se pueden detallar en la tabla II. DOI: https://doi.org/10.22463/0122820X.437
O.E Gualdrón, O.M Duque-Suárez y M.A. Chacón-Rojas, “Diseño de un sistema de reconocimiento de rostros mediante la hibridación de técnicas de reconocimiento de patrones, visión artificial EIA,enfocado a la seguridad e interacción robótica social, Mundo Fesc, Vol. 3, No. 6, pp. 16-28, 2013.
Y. Medina y H. Miranda, “Comparación de algoritmos basados en la criptografía simétrica DES, AES y 3DES”, Mundo FESC, vol. 5, no. 9, pp. 14-21, 2015.
A. Ollero-Baturone, Robótica: manipuladores y robots móviles, Barcelona, España: MARCOMBO S.A, 2001.
V.R Barrientos, J.R García Sánchez, y R. Silva Ortigoza, “Robots Móviles: Evolución y Estado del Arte”. Polibits, vol. 35, pp. 12-17, 2007. doi: 10.17562/PB-35-3. DOI: https://doi.org/10.17562/PB-35-3
N. Hernández y A. Flórez-Fuentes, "Computación en la Nube", Mundo Fesc, vol. 4, n.º 8, pp. 46-51, dic. 2014.
J. Engel and T. Schops, “LSD_SLAM desarrollado en la Universidad Técnica de Múnich (TUM)”, 2014. [En línea]. Disponible en: http://tracserver.labc.usb.ve/trac/visualslam/ wiki/An%C3%A1lisisComparativo
“ROS”, ROS.ORG, 2018. [Online]. Available: http://wiki.ros.org/ROS/Introduction
J. Engel, “Visual SLAM and VO: Surreal Vision, Oculus Research”, 2015 [presentation in People @EECS, UC Berkeley]. Available: https://people.eecs.berkeley.edu/~chaene/ /SLAM.pdf.
B. Davison, “Real-time simultaneous localisation and mapping with a single camera”, Proceedings Ninth IEEE International Conference on Computer Vision,
vol. 2, pp. 1403-1410, 2003. doi: 10.1109/ ICCV.2003.1238654
M. Shridhar and K.Y Neo, “Monocular SLAM for Real-Time Applications on Mobile Platforms”, 2015. [Online]. Available: https://
pdfs.semanticscholar.org/
J. Zijlmans, “LSD-slam and ORB-slam2, a literature based explanation”, 2017. [Online]. Available: https://medium.com/@j.zijlmans/ lsd-slam-vs-orb-slam2-a-literature-basedcomparison-20732df431d
E. Jakob, and D. Cremers, “LSD-SLAM: Large-Scale Direct Monocular SLAM”, 2017. here: DSO: Direct Sparse Odometry, https://vision.in.tum.de/research/vslam/ lsdslam?redire.
A. Villarroel, “Implementación de un sistema de mapeo 3D para inspección de sitios remotos utilizando un Cuadricoptero”, trabajo de fin de grado, Universidad Simón Bolívar, Sartenejas, 2015.
J. García-Merino, “Sistema avanzado de detección de obstáculos y navegación autónoma para vigilancia y protección basado en flota de vehículos aéreos no tripulados”, tesis doctoral, Universidad de Málaga, 2016.
Canónigo, “El aprendizaje en la era digital. Perspectivas desde las principales teorías”, Aibi revista de investigación, administración e ingeniería, vol. 5, nº 2, pp. 29-33., 2017 DOI: https://doi.org/10.15649/2346030X.439
The SLAM is one of the algorithms that were born with the intention of being able to position the
robot in an unknown environment while navigating through it and using the above information from
its sensors to build a map of the environment in which it is located. . To achieve the mapping, several
investigations have used sensors of ultrasound type, LIDAR, even cameras using artificial vision. The
objective of this research is focused on applying a SLAM technique on a mobile robotic platform. To
achieve this objective, a study is made of different existing SLAM methodologies that could meet the
expectations resulting in the LSD-SLAM, which with a suitable camera is able to obtain a semi-dense
3D map of the environment in which it works. It also develops in ROS (Robot Operating System) defined
as operating system, which should be taken into account for future research thanks to its great features.
Once researched, selected and implemented, the programming of the system was started by means of
tools and libraries which have support, in terms of reliable documentation and previously programmed
for their use.
Keywords: Laptop, cooling, HUB-USB, Master Cooler.
E. Rúa, A. Barrera, y N. Moreno, “Aprendizaje interactivo de Termodinámica de fluidos apoyado en las tecnologías de la información y comunicación”, Respuestas, vol. 19, no. 2, pp. 41-50, 2014.Diseño e implementación de un sistema de visión artificial usando una técnica de mapeo y localización simultánea (SLAM) sobre una plataforma robótica móvil se pueden detallar en la tabla II. DOI: https://doi.org/10.22463/0122820X.437
O.E Gualdrón, O.M Duque-Suárez y M.A. Chacón-Rojas, “Diseño de un sistema de reconocimiento de rostros mediante la hibridación de técnicas de reconocimiento de patrones, visión artificial EIA,enfocado a la seguridad e interacción robótica social, Mundo Fesc, Vol. 3, No. 6, pp. 16-28, 2013.
Y. Medina y H. Miranda, “Comparación de algoritmos basados en la criptografía simétrica DES, AES y 3DES”, Mundo FESC, vol. 5, no. 9, pp. 14-21, 2015.
A. Ollero-Baturone, Robótica: manipuladores y robots móviles, Barcelona, España: MARCOMBO S.A, 2001.
V.R Barrientos, J.R García Sánchez, y R. Silva Ortigoza, “Robots Móviles: Evolución y Estado del Arte”. Polibits, vol. 35, pp. 12-17, 2007. doi: 10.17562/PB-35-3. DOI: https://doi.org/10.17562/PB-35-3
N. Hernández y A. Flórez-Fuentes, "Computación en la Nube", Mundo Fesc, vol. 4, n.º 8, pp. 46-51, dic. 2014.
J. Engel and T. Schops, “LSD_SLAM desarrollado en la Universidad Técnica de Múnich (TUM)”, 2014. [En línea]. Disponible en: http://tracserver.labc.usb.ve/trac/visualslam/ wiki/An%C3%A1lisisComparativo
“ROS”, ROS.ORG, 2018. [Online]. Available: http://wiki.ros.org/ROS/Introduction
J. Engel, “Visual SLAM and VO: Surreal Vision, Oculus Research”, 2015 [presentation in People @EECS, UC Berkeley]. Available: https://people.eecs.berkeley.edu/~chaene/ /SLAM.pdf.
B. Davison, “Real-time simultaneous localisation and mapping with a single camera”, Proceedings Ninth IEEE International Conference on Computer Vision,
vol. 2, pp. 1403-1410, 2003. doi: 10.1109/ ICCV.2003.1238654
M. Shridhar and K.Y Neo, “Monocular SLAM for Real-Time Applications on Mobile Platforms”, 2015. [Online]. Available: https://
pdfs.semanticscholar.org/
J. Zijlmans, “LSD-slam and ORB-slam2, a literature based explanation”, 2017. [Online]. Available: https://medium.com/@j.zijlmans/ lsd-slam-vs-orb-slam2-a-literature-basedcomparison-20732df431d
E. Jakob, and D. Cremers, “LSD-SLAM: Large-Scale Direct Monocular SLAM”, 2017. here: DSO: Direct Sparse Odometry, https://vision.in.tum.de/research/vslam/ lsdslam?redire.
A. Villarroel, “Implementación de un sistema de mapeo 3D para inspección de sitios remotos utilizando un Cuadricoptero”, trabajo de fin de grado, Universidad Simón Bolívar, Sartenejas, 2015.
J. García-Merino, “Sistema avanzado de detección de obstáculos y navegación autónoma para vigilancia y protección basado en flota de vehículos aéreos no tripulados”, tesis doctoral, Universidad de Málaga, 2016.
Canónigo, “El aprendizaje en la era digital. Perspectivas desde las principales teorías”, Aibi revista de investigación, administración e ingeniería, vol. 5, nº 2, pp. 29-33., 2017 DOI: https://doi.org/10.15649/2346030X.439
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