Advertisement

Study of the Navigation Parameters in Appearance-Based Navigation of a Mobile Robot

  • Luis Payá
  • Oscar Reinoso
  • Arturo Gil
  • Nicolás García
  • Maria Asunción Vicente
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3617)

Abstract

Recently, appearance-based approaches have attracted the interests of computer vision researchers. Based on this idea, an appearance-based navigation method using the View-Sequenced Route-Representation model is proposed. A couple of parallel cameras is used to take low-resolution fontal images along the route to follow. Then, zero mean cross correlation is used as image comparison criterion to perform auto-location and control of the robot using only visual information. Besides, a sensibility analysis of the navigation parameters has been carried out to try to optimize the accuracy and the speed in route following. An exhaustive number of experiments using a 4-wheel drive robot with synchronous drive kinematics have been carried out.

Keywords

Mobile Robot Current Image Visual Servoing Proceeding IEEE Autonomous Navigation 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

References

  1. 1.
    Artac, M., Jogan, M., Leonardis, A.: Mobile robot localization using an incremental eigenspace model. In: Proceedings of the IEEE International Conference on Robotics & Automation, pp. 1025–1030 (2002)Google Scholar
  2. 2.
    Jones, S.D., Andersen, C., Crowley, J.L.: Appearance based processes for visual navigation. In: Proceedings of the IEEE International Conference on Intelligent Robots and Systems, pp. 551–557 (1997)Google Scholar
  3. 3.
    Kosaka, A., Kak, A.C.: Fast vision-guided mobile robot navigation using model-based reasoning and prediction of uncertainties. Computer Vision, Graphics and Image Processing: Image Understanding 56(3), 271–329 (1992)zbMATHGoogle Scholar
  4. 4.
    Lebegue, X., Aggarwal, J.K.: Significant line segments for an indoor mobile robot. IEEE Transactions on Robotics and Automation 9(6), 801–815 (1993)CrossRefGoogle Scholar
  5. 5.
    Lewis, J.P.: Fast normalized cross-correlation. Expanded version of paper from Vision Interface, 120–123 (1995)Google Scholar
  6. 6.
    Maeda, S., Kuno, Y., Shirai, Y.: Active navigation vision based on eigenspace analysis. In: Proceedings IEEE International Conference on Intelligent Robots and Systems, vol. 2, pp. 1018–1023 (1997)Google Scholar
  7. 7.
    Matsumoto, Y., Ikeda, K., Inaba, M., Inoue, H.: Visual navigation using omnidirectional view sequence. In: Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 317–322 (1999)Google Scholar
  8. 8.
    Matsumoto, Y., Inaba, M., Inoue, H.: Visual navigation using view-sequenced route representation. In: Proceedings of IEEE International conference on Robotics and Automation, vol. 1, pp. 83–88 (1996)Google Scholar
  9. 9.
    Ohno, T., Ohya, A., Yuta, S.: Autonomous navigation for mobile robots referring pre-recorded image sequence. In: Proceedings IEEE International Conference on Intelligent Robots and Systems, vol. 2, pp. 672–679 (1996)Google Scholar
  10. 10.
    Regini, L., Tascini, G., Zingaretti, P.: Appearance-based robot navigation. In: Proceedings of the Workshop su agenti robotici, Associazione Italiana per l’Intelligenze Artificiale, VIII Convegno (2002)Google Scholar
  11. 11.
    Santos-Victor, J., Sandini, G., Curotto, F., Garibaldi, S.: Divergent stereo for robot navigation: Learning from bees. In: Proceedings IEEE International conference con Computer Vision and Pattern Recognition, pp. 434–439 (1993)Google Scholar
  12. 12.
    Swain-Oropeza, R., Devy, M., Cadenat, V.: Controlling the execution of a visual servoing task. Journal of Intelligent and Robotic Systems 25(4), 357–369 (1999)CrossRefGoogle Scholar
  13. 13.
    Ulrich, I., Nourbakhsh, I.: Appearance-based place recognition for topological localization. In: Proceedings IEEE International Conference on Robotics and Automation, pp. 1023–1029 (2000)Google Scholar
  14. 14.
    Winters, N., Santos-Victor, J.: Information Sampling for optimal image data selection. In: Proceed. of the 9th International Symposium on Intelligent Robotics Systems, pp. 249–257 (2001)Google Scholar
  15. 15.
    Zhou, C., Wei, T., Tan, T.: Mobile robot self-localization based on global visual appearance features. In: Proceedings of the 2003 IEEE International Conference on Robotics & Automation, pp. 1271–1276 (2003)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Luis Payá
    • 1
  • Oscar Reinoso
    • 1
  • Arturo Gil
    • 1
  • Nicolás García
    • 1
  • Maria Asunción Vicente
    • 1
  1. 1.Departamento de Ingeniería de Sistemas IndustrialesMiguel Hernández UniversityElche (Alicante)Spain

Personalised recommendations