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Mobile Robots and EEG - A Review

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Research and Development in Intelligent Systems XXIV (SGAI 2007)

Abstract

In this paper we present an overview of recent methods of controlling mobile robots with emphasis on evolutionary approaches of robot control. Development of recent electroencephalogram (EEG) based Brain-computer interfaces (BCI) are discussed with the main reference to EEG analysis where brain electrical activity is classified with the intent of generating output commands. Recent attempts to control a mobile robot with a BCI are discussed with future plans for further research in this field.

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References

  1. Amai, W., Fahrenholtz, J., Leger, C. Hands-Free Operation of a Small Mobile Robot, Autonomous Robots July 2001, 11 (1) pp. 69 - 76.

    Google Scholar 

  2. Beer, R.D., Gallagher, J.C. (1992). Evolving dynamical neural networks for adaptive behaviour. Adaptive Behavior 1 (1) pp. 91-122.

    Article  Google Scholar 

  3. Beer, R.D, Toward the Evolution of Dynamical Neural Networks for Minimally Cognitive Behavior, In P. Maes, M. Mataric, J. Meyer, J. Pollack and S. Wilson (Eds.), From animals to animats 4: Proceedings Bajaj of the Fourth International Conference on Simulation of Adaptive Behavior, 1992 pp. 421-429. MIT Press.

    Google Scholar 

  4. Brooks, R.A. The Role of Learning in Autonomous Robots. Proceedings of the Fourth Annual Workshop on Computational Learning Theory (COLT ’91), Santa Cruz, CA, Morgan Kaufmann Publishers, August 1991, pp. 5-10.

    Google Scholar 

  5. Fabiani, G.E.; McFarland, D.J.; Wolpaw, J.R.; Pfurtscheller, G. Conversion of EEG activity into cursor movement by a brain-computer interface (BCI). IEEE Transactions on Neural Systems and Rehabilitation Engineering. Sept. 2004. 12 (3) pp 331 - 338.

    Article  Google Scholar 

  6. Floreano, D. and Mondada, F. Evolution of Homing Navigation in a Real Mobile Robot. IEEE Transactions on Systems, Man, and Cybernetics - Part B: Cybernetics. 1996. 26 (3) pp. 396-407.

    Article  Google Scholar 

  7. Floreano, D., Godjevac, J., Martinoli, A., Mondada, F. and Nicoud, J.D. Design, Control, and Applications of Autonomous Mobile Robots. In Advances in Intelligent Autonomous Agents, Boston: Kluwer Academic Publishers, 1998.

    Google Scholar 

  8. Floreano, D. and Mondada, F. Evolutionary Neurocontrollers for Autonomous Mobile Robots. Neural Networks. 1998. 11 (7-8) pp 1461-1478.

    Article  Google Scholar 

  9. Goldberg, D.E. Genetic Algorithms in search, optimization and machine learning. Reading MA: Addison-Wesley. 1989.

    Google Scholar 

  10. Holland, J.H. Adaptation in Natural and Artificial Systems. Ann Arbor, MI: University of Michigan Press. 1975.

    Google Scholar 

  11. Kosko, B. Neural Networks and Fuzzy Systems. Prentice-Hall 1994.

    Google Scholar 

  12. Tanaka,K.,Matsunaga,K.,Kanamori,N.,Hori,S.,Wang,H.O. Electroencephalogram-based control of a mobile robot. In Computational Intelligence, Robotics and Automation, July 2003, 2 (16-20) pp 688 - 693.

    Article  Google Scholar 

  13. Tanaka, K., Matsunaga, K., Wang, H.O. Electroencephalogram-Based Control of an Electric Wheelchair. Robotics, IEEE Transactions on Robotics and Automation. Aug. 2005. 21 (4) pp 762-766.

    Google Scholar 

  14. Maes, P. and R. A. Brooks, Learning to Coordinate Behaviors. AAAI, Boston, MA, August 1990 pp. 796-802.

    Google Scholar 

  15. Millan, J., Renkens, F., Mourino, J., Gerstner, Wulfram. Non-Invasive Brain-Actuated Control of a Mobile Robot. Proceedings of the 18th International Joint Conference on Artificial Intelligence, Acapulco, Mexico. August 2003.

    Google Scholar 

  16. Millan, J., Renkens, F., Mourino, J., Gerstner, Wulfram. Brain-actuated interaction. Artificial Intelligence. November 2004. 159 (1-2) pp. 241 - 259.

    Article  Google Scholar 

  17. Nelson, A.L. Grant, E. Barlow, G. White, M. Evolution of Complex Autonomous Robot Behaviors using Competitive Fitness. Integration of Knowledge Intensive Multi-Agent Systems. Oct 2003. pp. 145 - 150.

    Google Scholar 

  18. Nelson, A.L., Grant, E., Galeotti, J.M., Rhody, S. Maze Exploration Behaviors using an Integrated Evolutionary Robotics Environment. Robotics and Autonomous Systems, 2004. 46 (3) pp. 159-173.

    Article  Google Scholar 

  19. Nolfi, S., Floreano, D., Miglino, O. and Mondada, F. How to Evolve Autonomous Robots: Different Approaches in Evolutionary Robotics. 4th International Workshop on Artificial Life. 1994.

    Google Scholar 

  20. Ricardo A. Tellez, C.A., Evolving Cooperation of Simple Agents for the Control of an Autonomous Robot. Proceedings of the 5th IFAC Symposium on Intelligent Autonomous Vehicles (IAV04) Lisbon, Portugal, 2004.

    Google Scholar 

  21. Tanev, Ivan., Brzozowski, Michael., Shimohara, Katsunori. Evolution, Generality and Robustness of Emerged Surrounding Behavior in Continuous Predators-Prey Pursuit Problem in Genetic Programming and Evolvable Machines. September 2005. 6(3) pp. 301-318.

    Google Scholar 

  22. Wiering, M., Salustowicz, R. Schmidhuber, J. Model-based reinforcement learning for evolving soccer strategies. In Computational Intelligence in Games, chapter 5. Editors N. Baba and L. Jain. 2001 pp. 99-131.

    Google Scholar 

  23. Wolpaw, J.R, Birbaumer, N., McFarland, D.J., Pfurtscheller, G., Vaughan, T.M. Brain- computer interfaces for communication and control. Clinical Neurophysiology. 2002. 113 pp. 767-791.

    Article  Google Scholar 

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© 2008 Springer-Verlag London Limited

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Plant, K.A., Ponnapalli, P., Southall, D. (2008). Mobile Robots and EEG - A Review. In: Bramer, M., Coenen, F., Petridis, M. (eds) Research and Development in Intelligent Systems XXIV. SGAI 2007. Springer, London. https://doi.org/10.1007/978-1-84800-094-0_28

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  • DOI: https://doi.org/10.1007/978-1-84800-094-0_28

  • Publisher Name: Springer, London

  • Print ISBN: 978-1-84800-093-3

  • Online ISBN: 978-1-84800-094-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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