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Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 429))

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Abstract

Although sonars are among the most popular elements used in intelligent navigation vehicles, they still have unexplored specifics offering useful information. In this paper, we present further results of experiments focused on the exploration of sonars’ drawbacks. We combined the regular information obtained from a simple sonar system with information derived from measurement abnormalities and thus achieved an extended recognition effectiveness of the sonar system, which better distinguished the experimental shapes. The main objective of this paper is to calculate the effectiveness of identification using the ratio of parallelepipeds to cylinders and the average values of certain sequences of measurements. Further work targeted several navigation tasks on a real-time robot on an HCR base. Besides the implementation of map building with a relative degree of confidence, we performed experiments in rapid localization algorithm, which was developed simultaneously in our work group.

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References

  1. Dimitrova-Grekow, T., Jarczeweski, M.: Sonar method of distinguishing objects based on reflected signal specifics. In: LNCS, vol. 8502, pp 506–511. Springer, Berlin (2014)

    Google Scholar 

  2. Dimitrova-Grekow T.: A hybrid algorithm for self-location. In: PAK, vol. 11, pp. 1163–1166 (2013)

    Google Scholar 

  3. Ohtani, K., Baba, M.: Shape recognition for transparent objects using ultrasonic sensor array. In: SICE, Annual Conference, pp. 1813–1818 (2007)

    Google Scholar 

  4. Barshan, B., Kuc, R.: A bat-like sonar system for obstacle localization. Pattern Anal. Mach. Intell. 12, 686–690 (1992)

    Google Scholar 

  5. Walter, S.: The sonar ring: obstacle detection for a mobile robot. Robot. Autom. IEEE J. 4, 1574–1579 (1987)

    Google Scholar 

  6. Lenser, S., Veloso, M.: Visual sonar: fast obstacle avoidance using monocular vision. Intell Robot. Syst 1, 886–891 (2003)

    Google Scholar 

  7. Del Castilloa, G., Skaara, S., Cardenasb, A., Fehr, L.: A sonar approach to obstacle detection for a vision-based autonomous wheelchair. Robot. Autom. IEEE J. 54, 967–981 (2006)

    Google Scholar 

  8. Kiyoshi, O., Masamichi, M., Hiroyuki, T., Keihachiro, T.: Obstacle arrangement detection using multichannel ultrasonic sonar for indoor mobile robots. J. Artif. Life Robot. 15, 229–233 (2010)

    Article  Google Scholar 

  9. Dimitrova-Grekow, T., Zach, M.: Topological-metric indoor path planning. In: PAK Pomiary, Automatyka, Kontrola, vol. 58, pp. 611–618 (2012)

    Google Scholar 

  10. Fromberger, L.: Representing and selecting landmarks in autonomous learning of robot navigation. In: Xiong et al. C. (ed.) ICIRA Part I, LNAI vol. 5314, pp. 488–497. Springer, Berlin (2008)

    Google Scholar 

  11. Yap, TN., Shelton, CR.: SLAM in large indoor environments with low-cost, noisy, and sparse sonars. In: Proceedings of IEEE International Conference on Robotics and Automation, pp. 1395–401 (2009)

    Google Scholar 

  12. Joong-Tae, P., Jae-Bok, S., Se-Jin Lee, M.K.: Sonar sensor-based efficient exploration method using sonar salient features and several gains. J. Intell. Robot. Syst. 63, 465–480 (2011)

    Article  Google Scholar 

  13. Dimitrova-Grekow, T., Jarczeweski, M.: Identification effectiveness of the shape recognition method based on sonar. In: LNCS, vol. 9339, pp. 244–254, Springer, Berlin (2015)

    Google Scholar 

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Acknowledgments

This paper is supported by the S/WI/1/2013.

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Correspondence to Teodora Dimitrova-Grekow .

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Dimitrova-Grekow, T., Jarczewski, M. (2016). Extended Recognition Effectiveness of a Sonar System. In: Borzemski, L., Grzech, A., Świątek, J., Wilimowska, Z. (eds) Information Systems Architecture and Technology: Proceedings of 36th International Conference on Information Systems Architecture and Technology – ISAT 2015 – Part I. Advances in Intelligent Systems and Computing, vol 429. Springer, Cham. https://doi.org/10.1007/978-3-319-28555-9_13

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  • DOI: https://doi.org/10.1007/978-3-319-28555-9_13

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