Aplicación de un EIF-SLAM en entornos agrícolas basado en detección de troncos de árboles

• Autores: Fernando A. Auat Cheein, Guillermo Steiner, Gonzalo Perez Paina
• Localización: Ciencia y tecnología, ISSN 1850-0870, ISSN-e 2344-9217, Nº. 11, 2011, págs. 201-219
• Idioma: español
• DOI: 10.18682/cyt.v1i11.755
• Enlaces
  • Texto completo
• Resumen

  • En este trabajo se presenta la implementación de un algoritmo de SLAM (por sus siglas en inglés de Simultaneous Localization and Mapping) en un Filtro Extendido de Información para ambientes agrícolas (plantación de olivos). El algoritmo de SLAM se encuentra implementado en un robot unmanned tipo car-like no-holonómico. El mapeo del ambiente se basa en la implementación de máquinas de soporte vectorial (SVM, por sus siglas en inglés de Support Vector Machine) para la extracción de troncos asociados a los olivos del entorno. Este trabajo incluye resultados experimentales de implementación en entornos agrícolas reales.

• Referencias bibliográficas
  • R. Chatila and J. P. Laumond, “Position referencing and consistent world modeling for mobile robots,” Proc. of the IEEE International Conference...
  • N. Ayache and O. Faugeras, “Maintaining a representation of the environment of a mobile robot,” IEEE Transactions on Robotics and Automation,...
  • H. D. Whyte and T. Bailey, “Simultaneous localization and mapping (slam): part i essential algorithms,” IEEE Robotics and Automation Magazine,...
  • H. Whyte and T. Bailey, “Simultaneous localization and mapping (slam): part ii state of the art,” IEEE Robotics and Automation Magazine, vol....
  • A. Garulli, A. Giannitrapani, A. Rosi, and A. Vicino, “Mobile robot slam for line- based environment representation,” IEEE Conference on Decision...
  • J. Guivant, E. Nebot, and S. Baiker, “High accuracy navigation using laser range sensors in outdoor applications,” in Robotics and Automation,...
  • S. Thrun, W. Burgard, and D. Fox, Probabilistic Robotics. Cambridge: MIT Press, 2005.
  • C. Cadena and J. Neira, “Slam in o(log n) with the combined kalman - information ilter,” in Intelligent Robots and Systems, 2009. IROS 2009....
  • G. Dissanayake, P. Newman, S. Clark, H. F. Durrant-Whyte, and M. Csorba, “A solution to the simultaneous localisation and map building (slam)...
  • G. R. C. and W. R. E., Digital Image Processing. Addison-Wesley Publishing Company, 1993.
  • H. S., Neural Networks: A comprehensive foundation. Prentice Hall, 1999.
  • N. He, J. Cao, and L. Song, “Scale space histogram of oriented gradients for human detection,” vol. 2, dec. 2008, pp. 167 –170.
  • F. A. Auat Cheein, F. di Sciascio, G. Scaglia, and R. Carelli, “Towards features updating selection based on the covariance matrix of the...
  • D. A. Harville, Matrix Algebra from a Statistician’s Perspectiv. New York: Springer-Verlag, 1997.
  • F. A. Auat Cheein, Simultaneous Localization and Mapping of a Mobile Robot based on Uncertainty Zones Navigation. San Juan Argentina: PhD...
  • C. K. Li and R. Mathias, “The determinant of the sum of two matrices,” Bull. Austral. Math. Soc., vol. 52, pp. 425–429, 1995.
  • F. Masson, J. Guivant, J. Nieto, and E. Nebot, “The hybrid metric map: a solution for precision farming,” Latin American applied research,...
  • N. Dalal and B. Triggs, “Histograms of oriented gradients for human detection,” in CVPR ‘05: Proceedings of the 2005 IEEE Computer Society...
  • D. G. Lowe, “Distinctive image features from scale-invariant keypoints,” Int. J. Comput. Vision, vol. 60, no. 2, pp. 91–110, 2004.
  • V. N. Vapnik, Statistical Learning Theory. Wiley-Interscience, 1998.
  • K.-R. Muller, S. Mika, G. Ratsch, K. Tsuda, and B. Scholkopf, “An introduction to kernel based learning algorithms,” Neural Networks, IEEE...
  • Z. Zhang, “Flexible camera calibration by viewing a plane from unknown orientations,” in in ICCV, 1999, pp. 666–673.
  • R. Siegwart and I. Nourbahsh, Introduction to Autonomous Mobile Robots. Cambridge: MIT Press, 2004.