Advertisement

Design, Control, and Applications of Autonomous Mobile Robots

  • D. Floreano
  • J. Godjevac
  • A. Martinoli
  • F. Mondada
  • J.-D. Nicoud
Chapter
Part of the International Series on Microprocessor-Based and Intelligent Systems Engineering book series (ISCA, volume 18)

Abstract

An autonomous robot is a machine that operates in a partially unknown and unpredictable environment. In contrast to robots used in manufacturing plants, where the environment is highly controlled, autonomous robots cannot always be programmed to execute predefined actions because one does not know in advance what will be the universe of required sensorimotor transformations required by the various situations that the robot might encounter. Furthermore, the environment might have dynamic characteristics that require rapid online modifications in the robot behaviour. For these reasons, in the last ten years several researchers have looked at novel methods for setting up autonomous mobile robots.

Keywords

Membership Function Mobile Robot Fuzzy Controller Obstacle Avoidance Autonomous Robot 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    E. G. Bonabeau and Theraulaz G. Intelligence Collective. Hermès, Paris, France, 1994.Google Scholar
  2. 2.
    R. A. Brooks. A robust layered control system for a mobile robot. IEEE Robotics and Automation, RA-2:14-23, March 1986.Google Scholar
  3. 3.
    R. A. Brooks. Intelligence without representation. Artificial Intelligence, 47:139–159, 1991.CrossRefGoogle Scholar
  4. 4.
    D. Cliff, P. Husbands, J. A. Meyer, and S. W. Wilson, editors. From Animals to Animats: Proceedings of the Third International Conference on Simulation of Adaptive Behavior, Cambridge, MA, 1994. MIT Press/Bradford Books.Google Scholar
  5. 5.
    M. Dorigo. Special issue on learning autonomous robots. IEEE Transactions on Systems, Man and Cybernetics-Part B, 26:361–364, 1993.Google Scholar
  6. 6.
    M. Dorigo and U. Schnepf. Genetic-based machine learning and behavior based robotics: a new synthesis. IEEE Transactions on Systems, Man and Cybernetics, 23:141–154, 1993.CrossRefGoogle Scholar
  7. 7.
    D. Floreano and F. Mondada. Automatic Creation of an Autonomous Agent: Genetic Evolution of a Neural-Network Driven Robot. In D. Cliff, P. Husbands, J. Meyer, and S. W. Wilson, editors, From Animals to Animats III: Proceedings of the Third International Conference on Simulation of Adaptive Behavior, pages 402–410. MIT Press-Bradford Books, Cambridge, MA, 1994.Google Scholar
  8. 8.
    D. Floreano and F. Mondada. Evolution of homing navigation in a real mobile robot. IEEE Transactions on Systems, Man, and Cybernetics-Part B, 26:396–407, 1996.CrossRefGoogle Scholar
  9. 9.
    D. Floreano and F. Mondada. Evolution of plastic neurocontrollers for situated agents. In P. Maes, M. Mataric, J-A. Meyer, J. Pollack, H. Roitblat, and S. Wilson, editors, From Animals to Animats IV: Proceedings of the Fourth International Conference on Simulation of Adaptive Behavior, pages 402–410. MIT Press-Bradford Books, Cambridge, MA, 1996.Google Scholar
  10. 10.
    D. Floreano and S. Nolfi. Adaptive behavior in competing co-evolving species. In P. Husbands and I. Harvey, editors, Proceedings of the 4th European Conference on Artificial Life, Cambridge, MA, 1997. MIT Press.Google Scholar
  11. 11.
    D. Floreano and S. Nolfi. God save the red queen! competition in co-evolutionary robotics. In J. Koza, K. Deb, M. Dorigo, D. Fogel, M. Garzon, H. Iba, and R. L. Riolo, editors, Proceedings of the 2nd International Conference on Genetic Programming, San Mateo, CA, 1997. Morgan Kaufmann.Google Scholar
  12. 12.
    N. Franceschini, J.-M. Pichon, and C. Blanes. Real time visuomotor control: From flies to robots. In Proceedings of the Fifth International Conference on Advanced Robotics, pages 91–95, Pisa, June 1991.Google Scholar
  13. 13.
    M. Fujita and K. Kageyama. An open architecture for robot entertainment. In ACM Conference on Autonomous Agents, pages 435–442, Marina Del Rey, February 1997.Google Scholar
  14. 14.
    P. Gaussier. Special Issue on Animat Approach to Control Autonomous Robots interacting with an unknown world. Robotics and Autonomous Systems, 16, 1995.Google Scholar
  15. 15.
    J. Godjevac. A Method for the Design of Neuro-Fuzzy Controllers; an Application in Robot Learning. PhD Thesis N° 1602, École Polytechnique Fédérale de Lausanne, 1997.Google Scholar
  16. 16.
    T. Gomi and K. Ide. The development of an intelligent wheelchair. In Intelligent Vehicles Symposium, Tokyo, 1996.Google Scholar
  17. 17.
    H. Greiner, C. Angle, T. Freed, J. Jones, P. Ning, R. Elsley, and G. Bane. Autonomous legged underwater vehicles for near land warfare. In Autonomous Vehicles in Mine Counter-measures Symposium, pages 14–22, Monterey, CA, 1995.Google Scholar
  18. 18.
    J. H. Holland. Adaptation in natural and artificial systems. The University of Michigan Press, Ann Arbor, 1975.Google Scholar
  19. 19.
    N. Jakobi. Half-baked, ad-hoc and noisy: Minimal simulations for evolutionary robotics. In P. Husbands and I. Harvey, editors, Proceedings of the 4th European Conference on Artificial Life, Cambridge, MA, 1997. MIT Press.Google Scholar
  20. 20.
    A. Kelly and A. Stenz. Analysis of requirements for high speed rough terrain autonomous mobile robots. In IEEE Conference on Robotics and Automation, pages 3318–3333, Albuquerque, 1997.Google Scholar
  21. 21.
    P. Maes, M. Mataric, J-A. Meyer, J. Pollack, H. Roitblat, and S. Wilson, editors. From Animals to Animats: Proceedings of the Fourth International Conference on Simulation of Adaptive Behavior, Cambridge, MA, 1996. MIT Press/Bradford Books.Google Scholar
  22. 22.
    A. Martinoli, E. Franzi, and O. Matthey. Towards a reliable set-up for bio-inspired collective experiments with real robots. In Proc. of the Fifth International Symposium on Experimental Robotics ISER-97, Barcelona, Spain, June 1997. In Press.Google Scholar
  23. 23.
    A. Martinoli and F. Mondada. Collective and cooperative group behaviours: Biologically inspired experiments in robotics. In Proceedings of the Fourth International Symposium on Experimental Robotics, Stanford, U.S.A., 1995. Springer Verlag.Google Scholar
  24. 24.
    A. Martinoli, M. Yamamoto, and F. Mondada. On the modelling of bioinspired collective experiments with real robots. In Proceedings of the Fourth European Conference on Artificial Life ECAL-97, Brighton, UK, July 1997. http://www.cogs.susx.ac.uk/eca197/present.html.
  25. 25.
    M. J. Mataric. Learning in multi-robot systems. In G. Weiss and S. Sen, editors, Adaptation and Learning in Multi-Agent Systems, volume 1042, pages 152–163. Springer Verlag, Lecture Notes in Artificial Intelligence, 1996.Google Scholar
  26. 26.
    J. A. Meyer, H. L. Roitblat, and S. W. Wilson, editors. From Animals to Animats: Proceedings of the Second International Conference on Simulation of Adaptive Behavior, Cambridge, MA, 1993. MIT Press/Bradford Books.Google Scholar
  27. 27.
    J. A. Meyer and S. W. Wilson, editors. From Animals to Animats: Proceedings of the First International Conference on Simulation of Adaptive Behavior, Cambridge, MA, 1991. MIT Press/Bradford Books.Google Scholar
  28. 28.
    O. Michel. Evolutionary neurogenesis applied to mobile robotics. In M. Patel and V. Honovar, editors, Advances in Evolutionary Synthesis of Neural Systems. MIT Press, Cambridge, MA, 1997.Google Scholar
  29. 29.
    F. Mondada and D. Floreano. Evolution of neural control structures: some experiments on mobile robots. Robotics and Autonomous Systems, 16:183–195, 1995.CrossRefGoogle Scholar
  30. 30.
    F. Mondada, E. Franzi, and P. Ienne. Mobile robot miniaturization: A tool for investigation in control algorithms. In T. Yoshikawa and F. Miyazaki, editors, Proceedings of the Third International Symposium on Experimental Robotics, pages 501–513, Tokyo, 1993. Springer Verlag.Google Scholar
  31. 31.
    A. Murciano and J. del R. Millán. Learning signaling behaviors and specialization in cooperative agents. Adaptive Behavior, 5(1):5–28, 1997.CrossRefGoogle Scholar
  32. 32.
    J. D. Nicoud. Vehicles and robots for humanitarian demining. Industrial Robot Journal, 24(2):168, 1997.Google Scholar
  33. 33.
    S. Nolfi, D. Floreano, O. Miglino, and F. Mondada. How to evolve autonomous robots: Different approaches in evolutionary robotics. In R. Brooks and P. Maes, editors, Proceedings of the Fourth Workshop on Artificial Life, pages 190–197, Boston, MA, 1994. MIT Press.Google Scholar
  34. 34.
    S. W. Pacala, D. M. Gordon, and H. C. J. Godfray. Effects of social group size on information transfer and task allocation. Evolutionary Ecology, 10:127–165, 1996.CrossRefGoogle Scholar
  35. 35.
    L.E. Parker. The effect of action recognition and robot awareness in cooperative robotic teams. In Proceedings of IEEE International Conference on Intelligent Robots and Systems IROS-95, volume 1, pages 212–219, Pittsburgh, PA, August 1995. Springer Verlag.Google Scholar
  36. 36.
    R. Pfeifer. Cognition — perspectives from autonomous agents. Robotics and Autonomous Agents, 15:47–70, 1995.CrossRefGoogle Scholar
  37. 37.
    B. Saugy and R. Rovira. The Serpentine, a step forward in intelligent transport system. In Proceedings of the Conference on Robotics and Intelligent Systems (IROS97), Grenoble, France, September 1997.Google Scholar
  38. 38.
    L. Steels. The Artificial Life Roots of Artificial Intelligence. Artificial Life, 1:75–110, 1994.CrossRefGoogle Scholar
  39. 39.
    M. Sugeno and K. Murakami. An Experimental Study on Fuzzy Parking Control Using a Model Car. In Michio Sugeno, editor, Industrial Applications of Fuzzy Control, chapter 8, pages 125–138. North-Holland, 1985.Google Scholar
  40. 40.
    C. Versino and L. M. Gambardella. Ibots learn genuine team solutions. In M. Van Someren and G. Widmer, editors, Proceedings European Machine Learning ECML-97, pages 298–311, Kyoto, Japan, 1997. Springer Verlag. Lecture Notes in Artificial Intelligence.Google Scholar

Copyright information

© Springer Science+Business Media Dordrecht 1999

Authors and Affiliations

  • D. Floreano
    • 1
  • J. Godjevac
    • 1
  • A. Martinoli
    • 1
  • F. Mondada
    • 1
  • J.-D. Nicoud
    • 1
  1. 1.Swiss Federal Institute of Technology in Lausanne LAMI-INF-EPFLEcublensSwitzerland

Personalised recommendations