A Complete Sensor-based System to Navigate Through a Cluttered Environment

A. Durand-Petiteville, V. Cadenat, N. Ouadah

2015

Abstract

This article deals with the autonomous navigation problem of a mobile robot in a cluttered environment. We propose to have a different perspective than the traditional way of splitting the problem into two categories: the map-based ones and the mapless ones. Here we divide navigation systems into six processes: perception, modeling, localization, planning, action and decision. Then we present how those processes are organized into an architecture to perform a navigation. It is shown that this framework embraces any navigation system proposed in the literature and how it allows to create new combination of processes. We then detail our solution to the problem which mainly consists in coupling sensor-based controllers with a topological map. Moreover we present the used tools that we have developed over the last years as well as the ones from the literature. Finally we present experimentation results of a long-range navigation based on the proposed approach where a robot drives through an environement despite of occlusions and possible collisions due to obstacles.

References

  1. Bonin-Font, F., Ortiz, F., and Oliver, G. (2008). Visual navigation for mobile robots : a survey. Journal of intelligent and robotic systems, 53(3):263.
  2. Booij, O., Terwijn, B., Zivkovic, Z., and Krose, B. (2007). Navigation using an appearance based topological map. In IEEE Int. Conf. on Robotics and Automation, pages 3927- 3932, Rome, Italy.
  3. Cadenat, V., Folio, D., and Durand Petiteville, A. (2012). A comparison of two sequencing techniques to perform a vision-based navigation task in a cluttered environment. Advanced Robotics.
  4. Chaumette, F. and Hutchinson, S. (2006). Visual servo control, part 1 : Basic approaches. IEEE Robotics and Automation Magazine, 13(4).
  5. Cherubini, A. and Chaumette, F. (2013). Visual navigation of a mobile robot with laser-based collision avoidance. Int. Journal of Robotics Research, 32(2):189-209.
  6. Cherubini, A., Spindler, F., and Chaumette, F. (2011). A redundancy-based approach for visual navigation with collision avoidance. In Computational Intelligence in Vehicles and Transportation Systems (CIVTS), 2011 IEEE Symposium on, pages 8-15. IEEE.
  7. Choset, H., Lynch, K., Hutchinson, S., Kantor, G., Burgard, W., Kavraki, L., and Thrun, S. (2005). Principles of Robot Motion. MIT Press, Boston.
  8. Courbon, J., Mezouar, Y., and Martinet, P. (2009). Autonomous navigation of vehicles from a visual memory using a generic camera model. Intelligent Transport System (ITS), 10:392-402.
  9. Durand Petiteville, A., Durola, S., Cadenat, V., and Courdesses, M. (2013). Management of visual signal loss during image based visual servoing. In Control Conference (ECC), 2013 European, pages 2305-2310. IEEE.
  10. Durand Petiteville, A., Hutchinson, S., Cadenat, V., and Courdesses, M. (2011). 2d visual servoing for a long range navigation in a cluttered environment. In Decision and Control and European Control Conference (CDC-ECC), 2011 50th IEEE Conference on, pages 5677-5682. IEEE.
  11. Krajník, T. and Pr?euc?il, L. (2008). A simple visual navigation system with convergence property. In European Robotics Symposium 2008, pages 283-292. Springer.
  12. Matsumoto, Y., Inaba, M., and Inoue, H. (1996). Visual navigation using viewsequenced route representation. In IEEE Int. Conf. on Robotics and Automation, pages 83-88 -2692, Minneapolis, USA.
  13. Royer, E., Lhuillier, M., Dhome, M., and Lavest, J.-M. (2007). Monocular vision for mobile robot localization and autonomous navigation. International Journal of Computer Vision, 74(3):237-260.
  14. Samson, Borgne, and Espiau (1991). Robot control : The task function approach. Oxford science publications.
  15. Segvic, S., Remazeilles, A., Diosi, A., and Chaumette, F. (2009). A mapping and localization framework for scalable appearance-based navigation. Computer Vision and Image Understanding, 113(2):172-187.
  16. Souères, P. and Cadenat, V. (2003). Dynamical sequence of multi-sensor based tasks for mobile robots navigation. In SYROCO, Wroclaw, Poland.
  17. Souères, P., Hamel, T., and Cadenat, V. (1998). A path following controller for wheeled robots wich allows to avoid obstacles during the transition phase. In IEEE, Int. Conf. on Robotics and Automation, Leuven, Belgium.
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Paper Citation


in Harvard Style

Durand-Petiteville A., Cadenat V. and Ouadah N. (2015). A Complete Sensor-based System to Navigate Through a Cluttered Environment . In Proceedings of the 12th International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO, ISBN 978-989-758-123-6, pages 166-173. DOI: 10.5220/0005502201660173


in Bibtex Style

@conference{icinco15,
author={A. Durand-Petiteville and V. Cadenat and N. Ouadah},
title={A Complete Sensor-based System to Navigate Through a Cluttered Environment},
booktitle={Proceedings of the 12th International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO,},
year={2015},
pages={166-173},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005502201660173},
isbn={978-989-758-123-6},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 12th International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO,
TI - A Complete Sensor-based System to Navigate Through a Cluttered Environment
SN - 978-989-758-123-6
AU - Durand-Petiteville A.
AU - Cadenat V.
AU - Ouadah N.
PY - 2015
SP - 166
EP - 173
DO - 10.5220/0005502201660173