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Door Traversing for a Vision-Based Mobile Robot Using PCA

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Knowledge-Based Intelligent Information and Engineering Systems (KES 2005)

Abstract

This paper presents a method that a vision-based mobile robot can find location of doors and can safely traverse the door in complex environments. A robot must be able to find the door in order that it achieves the behavior that is scheduled after traversing a door. In this paper, PCA (Principal Component Analysis) algorithm using a vision sensor is used for a mobile robot to find the location of door. In addition, a fuzzy controller using a sonar data is used for a robot to avoid obstacles and traverse the door.

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References

  1. Monasterio, I., Lazkano, E.: Learning to Traverse Doors Using Visual Information. Mathematics and Computers in Simulation 60, 347–356 (2002)

    Article  MATH  MathSciNet  Google Scholar 

  2. Eberst, C., Andersson, M.: Vision-Based Door-Traversal for Autonomous Mobile Robots. In: International Conf. on Intelligent Robots and Systems, pp. 620–625 (2000)

    Google Scholar 

  3. Stoeter, A.: Real-time Door Detection in Cluttered Environments. In: International Symposium on Intelligent Control, July 2000, vol. 15, pp. 187–192 (2000)

    Google Scholar 

  4. Turk, M., Pentland, A.: Eigenfaces for recognition. J. Cognitive Neuroscience 3(1), 71–86 (1991)

    Article  Google Scholar 

  5. Kirby, M., Sirovich, L.: Application of The Karhunen-Loeve Procedure for The Characterization of Human Face. IEEE Trans. on PAMI 12, 103–108 (1990)

    Google Scholar 

  6. Yen, J., Pfluger, N.: Path Planning and Execution Using Fuzzy Logic. In: AIAA Guidance, Navigation and Control Conference, New Orleans LA, August 1991, vol. 3, pp. 1691–1698 (1991)

    Google Scholar 

  7. Reignier, P.: Fuzzy Logic Techniques for Mobile Robot Obstacle Avoidance. Robotics and Autonomous Systems 12, 143–153 (1994)

    Article  Google Scholar 

  8. Lee, P.S., Wang, L.L.: Collision Avoidance by Fuzzy Logic Control for Automated Guided Vehicle Navigation. Journal of Robotics Systems 11, 743–760 (1994)

    Article  MATH  Google Scholar 

  9. Beaufrer, B.: A Mobile Robot Navigation Method Using A Fuzzy Logic Approach. Robotica 13, 437–448 (1995)

    Article  Google Scholar 

  10. Yen, J., Pfluger, N.: A Fuzzy Logic Based Extension to Payton and Rosenblatt’s Command Fusion Method for Mobile Robot Navigation. IEEE Trans. Syst. Man, Cybern. 25(6), 971–978 (1995)

    Article  Google Scholar 

  11. Saffiotti, A.: The Uses of Fuzzy Logic in Autonomous Robot Navigation. Soft Computing 1, 180–197 (1997)

    Google Scholar 

  12. Montaner, M.B., Serrano, A.R.: Fuzzy Knowledge-based Controller Design for Autonomous Robot Navigation. Expert Systems with Application 14, 179–186 (1998)

    Article  Google Scholar 

  13. Maaref, H., Barret, C.: Sensor-based Fuzzy Navigation of An Autonomous Mobile Robot in An Indoor Environment. Control Engineering Practice 8, 747–768 (2000)

    Article  Google Scholar 

  14. Doitsodis, L., Valavanis, K.P., Tsourveloudis, N.C.: Fuzzy Logic Based Autonomous Skid Steering Vehicle Navigation. In: IEEE Int. Conf. on Robotics and Automation, Washington, DC, May 2002, vol. 2, pp. 2171–2177 (2002)

    Google Scholar 

  15. Pratihar, D.K., Dep, K., Ghosh, A.: A Genetic-Fuzzy Approach for Mobile Robot Navigation Among Moving Obstacles. International Journal of Approximate Reasoning 20, 145–172 (1999)

    Article  MATH  Google Scholar 

  16. Wang, J.S., Lee, C.S.: Self-Adaptive Recurrent Neural-Fuzzy Control for An Autonomous Underwater Vehicle. In: IEEE Int. Conf. on Robotics and Automation, Washington, DC, May 2002, vol. 2, pp. 1095–1100 (2002)

    Google Scholar 

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© 2005 Springer-Verlag Berlin Heidelberg

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Seo, MW., Kim, YJ., Lim, MT. (2005). Door Traversing for a Vision-Based Mobile Robot Using PCA. In: Khosla, R., Howlett, R.J., Jain, L.C. (eds) Knowledge-Based Intelligent Information and Engineering Systems. KES 2005. Lecture Notes in Computer Science(), vol 3684. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11554028_73

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  • DOI: https://doi.org/10.1007/11554028_73

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-28897-8

  • Online ISBN: 978-3-540-31997-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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