OBSTACLE DETECTION USING STRUCTURED BACKGROUND

Ghaida Al Zeer, Adnan Abou Nabout, Bernd Tibken

2009

Abstract

The paper presents an obstacle detection method for mobile robots using a structured background. This method is based on differences of appearance between obstacles and the background in the camera images. The basic idea is to cover the ground of the workspace with a known structure. If part of this structure is obscured, this can be detected and indicates the existence of an obstacle. The method uses a reference symbol, chosen to exhibit certain features, to construct a reference image of the structured background. To detect possible obstacles we calculate the Fourier descriptors (FD) of all contours included in a given image and compare them with those of the stored reference symbol. This enables us to recognize all reference symbols which are not obscured by obstacles. We then determine the positions and dimensions of all existing obstacles by calculating the occupied symbol areas. The method is implemented as part of a robot-vision system for fully automated stockkeeping. In this paper the results are shown using a MATLAB implementation.

References

  1. Al Zeer, G., Nabout, A., Tibken, B., Path Planning for Mobile Robots by Means of Approximate Routes, 2007 IEEE International Conference on Control and Automation, Guangzhou, CHINA, May 30 to June 1, 2007, pp. 2468-2473.
  2. Al Zeer G., Nabout, A., Tibken, B., Hindernisvermeidung für Mobile Roboter mittels Ausweichecken, 52nd Internationales Wissenschaftliches Kolloquium, Technische Universität Ilmenau, 10.-13. Sep. 2007, pp. 437-442.
  3. Al Zeer, G., Nabout, A., Tibken, B., Extended Method for Path Planning Using Auxiliary Corners, the 3rd IEEE International Conference on Information & Communication Technologies: from Theory to Application, ICTTA'08, 7-11 April 2008, Damascus - Syria.
  4. Borenstein, J., Koren, Y., Real time obstacle avoidance for fast mobile robots in cluttered environments. IEEE Conf. Robotics and Automation, pp. 572-577, 1990.
  5. Nabout A., Modulares Konzept und Methodik zur wissensbasierten Erkennung komplexer Objekte in CAQ-Anwendungen, 1993.
  6. Simmons. R., The Curvature-Velocity Method for Local Obstacle Avoidance. In Proc. IEEE Conf. Robotics and Automation, 1996.
  7. Sabe, K., Fukuch, M., Gutmann, J., Ohashi, T., Kawamoto K., Yoshigahara, T., Obstacle Avoidance and Path Planning for Humanoid Robots using Stereo Vision.Proceedings of the International Conf. on Robotics and Automation, ICRA'04, New Orleans, April 2004.
  8. Ulrich, I., Nourbakhsh, I., Appearance-Based Obstacle Detection with Monocular Color Vision, Proceedings of the AAAI National Conference on Artificial Intelligence, Austin, TX, July/August 2000.
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Paper Citation


in Harvard Style

Al Zeer G., Nabout A. and Tibken B. (2009). OBSTACLE DETECTION USING STRUCTURED BACKGROUND . In Proceedings of the 6th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO, ISBN 978-989-674-000-9, pages 439-444. DOI: 10.5220/0002209004390444


in Bibtex Style

@conference{icinco09,
author={Ghaida Al Zeer and Adnan Abou Nabout and Bernd Tibken},
title={OBSTACLE DETECTION USING STRUCTURED BACKGROUND},
booktitle={Proceedings of the 6th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO,},
year={2009},
pages={439-444},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002209004390444},
isbn={978-989-674-000-9},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 6th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO,
TI - OBSTACLE DETECTION USING STRUCTURED BACKGROUND
SN - 978-989-674-000-9
AU - Al Zeer G.
AU - Nabout A.
AU - Tibken B.
PY - 2009
SP - 439
EP - 444
DO - 10.5220/0002209004390444