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Autonomous Robots

, Volume 20, Issue 3, pp 239–249 | Cite as

Smell, think and act: A cognitive robot discriminating odours

  • Amy Loutfi
  • Silvia Coradeschi
Article

Abstract

In this paper, we explore the integration of an electronic nose and its odour discrimination functionalities into a multi-sensing robotic system which works over an extended period of time. The robot patrols an office environment, collecting odour samples of objects and performing user requested tasks. By considering an experimental platforms which operates over an extended period of time, a number of issues related to odour discrimination arise such as the drift in the sensor data, online learning of new odours, and the correct association of odour properties related to objects. In addition to an electronic nose our robotic system consists of other sensing modalities (vision and sonar), behaviour-based control and a high level symbolic planner.

Keywords

Electronic noses Odour discrimination Mobile olfaction Anchoring Planning for perceptual actions 

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References

  1. AppliedSensor 2000. AppliedSensor GmbH—Sensor modules. Online at http://www.appliedsensor.com.
  2. Broxvall, M., Coradeschi, S., Karlsson, L., and Saffiotti, A. 2005.Recovery planning for ambiguous cases in perceptual anchoring. In: Proc. of the 20th AAAI Conf. Pittsburgh, PA, AAAI Press. Online at http://www.aass.oru.se/~asaffio/.
  3. Coradeschi, S. and Saffiotti, A. 2000. Anchoring symbols to sensor data: Preliminary report.’ In Proc. of the 17th AAAI Conf. Menlo Park, CA, AAAI Press pp. 129–135,. Online at http://www.aass.oru.se/~asaffio/.
  4. Coradeschi, S. and Saffiotti, A. 2003.An introduction to the anchoring problem’. Robotics and Autonomous Systems, 43(2–3):85–96.Google Scholar
  5. Cyranose-Sciences 2000.The Cyranose 320 electronic nose’. Online at http://www.cyranose.com.
  6. Delpha, C., Lumbreras, M., and Siadat, M. 2001.Discrimination of Forane 134a and carbon dioxide concentrations in an air conditioned atmosphere with an electronic nose: influence of the relative humidity. Sensors and Actuators B Chemical, B80(1):59–67.Google Scholar
  7. Driankov, D. and Saffiotti, A. (eds.): 2001. Fuzzy Logic Techniques for Autonomous Vehicle Navigation, Studies in Fuzziness and Soft Computing. Springer-Phisica Verlag. ISBN 3-7908-1341-9.Google Scholar
  8. Dutta, R., Hines, L., Gardner, J., and Boilot, P. 2002. ‘Bacteria classification using Cyranose 320 electronic nose’. Biomedical Engineering Online 1.Google Scholar
  9. Gath, I. and Geva, A. 1989.Unsupervised optimal fuzzy clustering. IEEE Trans. on Pattern Analysis and Machine Intelligence, 11(7):773–781.Google Scholar
  10. Guardarrama, A., Fernandez, J., and Iniguez, M. 2001.Discrimination of wine aroma using an array of conducting polymer sensors in conjunction with solid-phase micro-extraction (SPME) technique. Sensors and Actuators-B Chemical, B77(1–2):401–408.Google Scholar
  11. Holmberg, M., Winquist, F., Lundström, Y., Davide, F., Natale, C.D., and D’Amico, A. 1996.Drift Counteraction for an electronic nose. Sensors and Actuators B, 35–36:528–535.Google Scholar
  12. Ishida, H., Suetsugu, K., Nakamoto, T., and Moriizumi, T. 1996:Study of autonomous mobile sensing system for localization of odor source using gas sensors and anemometric sensors. Sensors and Actuators A, 45:153–157.Google Scholar
  13. Karlsson, L. 2001.Conditional progressive planning under uncertainty. In: Proc. of the 17th Int. Joint Conferences on Artificial Intelligence (IJCAI). pp. 431–438.Google Scholar
  14. Kazadi, S., Goodman, R., Tsikata, D., Green, D., and Lin, H. 2000.An autonomous water vapor plume tracking robot using passive resistive polymer sensors. Autonomous Robots, 9(2):175–188.Google Scholar
  15. Keller, P., Kouzes, R., Kangas, L., and Hashem, S. 1995.Transmission of Olfactory Information for Telemedicine. Interactive Technology and the New Paradigm for Healthcare, pp. 168–172.Google Scholar
  16. Lilienthal, A.J. and Duckett, T. 2003.Creating gas concentration gridmaps with a mobile robot. In Proceedings of the 2003 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2003). pp. 118–123.Google Scholar
  17. Loutfi, A. and Coradeschi, S. 2004.Forming odour categories using an electronic nose. In Proc. of European Conference in Artificial Intelligence (ECAI 2004). pp. 119–124.Google Scholar
  18. Loutfi, A. and Coradeschi, S. 2005.Improving odour analysis through human robot interaction. In Proc of the IEEE International Conference on Robotics and Automation (ICRA 2005). Barcelona, Spain, pp. 4454–4460.Google Scholar
  19. Loutfi, A., Coradeschi, S., Karlsson, L., and Broxvall, M., 2005a. Object recognition: a new application for smelling robots. Robotics and Autonomous Systems, 52:272–289.Google Scholar
  20. Loutfi, A., Coradeschi, S., and Saffiotti, A. 2005b.Maintaining coherent perceptual information using anchoring. In The Nineteenth International Joint Conference on Artificial Intelligence (IJCAI ’05). Edinburgh, Scotland, pp. 1477–1482.Google Scholar
  21. Loutfi, A., Coradeschi, S., Karlsson, L., and Broxvall, M. 2004. Putting olfaction into action: Using an electronic nose on a multi-sensing mobile robot. In In Proc. IEEE International Conference on Intelligent Robots and Systems (IROS). pp. 337–342.Google Scholar
  22. Loutfi, A. and Wide, P. 2002.Symbolic estimation of food odors using fuzzy techniques.In Proc. Information and Processing and Managment of Uncertainty (IPMU). Annecy, France, pp. 919–926.Google Scholar
  23. Marques, L., Nunes, U., and de Almeida, A. 2002. Olfaction-based mobile robot navigation. Thin Solid Films, 418:51–58.Google Scholar
  24. Natale, C. D., Davide, F., and D’Amico, A. 1995. A self-organizing system for pattern classificiation: time varying statistics and sensor drift effects. Sensors and Actuators-B, 26–27:237–241.Google Scholar
  25. O’connell, M., Valdora, G., and Peltzer, G. 2001.A practical approach for fish freshness determinations using a portable electronic nose. Sensors and Actuators-B Chemical, B80(2):149–154.Google Scholar
  26. Persaud, K. and Dodd, G. 1982.Analysis of discrimination mechanisms of the mammalian olfactory system using a model nose. Nature, 299:352–355.Google Scholar
  27. Rochel, O., Martinez, D., Hugues, E., and Sarry, F. 2002. Stereo-olfaction with a sniffing neuromorphic robot using spiking neurons. In 16th European Conference on Solid-State Transducers - EUROSENSORS, Prague, Czech Republic.Google Scholar
  28. Russell, R., Thiel, D., and Mackay-Sim, A., 1994.Sensing odour trails for mobile robot navigation. In In IEEE Int. Conf. Robotics and Automation (ICRA 1994). pp. 2672–2677.Google Scholar
  29. Saffiotti, A., Konolige, K., and Ruspini, E. H. 1995. A multivalued-logic approach to integrating planning and control. Artificial Intelligence, 76(1–2):481–526.Google Scholar
  30. Xie, X. and Beni, G. 1991. A validity measure for fuzzy clustering. IEEE Trans. on Pattern Analysis and Machine Intelligence, 13(8):841–847.Google Scholar

Copyright information

© Springer Science + Business Media, LLC 2006

Authors and Affiliations

  1. 1.Center for Applied Autonomous Sensor SystemsÖrebro UniversityÖrebroSweden

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