THE ROLE OF SENSORY-MOTOR COORDINATION - Identifying Environmental Motion Dynamics with Dynamic Neural Networks

Stephen Paul McKibbin, Bala Amavasai, Arul N. Selvan, Fabio Caparrelli, W. A. F. W. Othman

Abstract

We describe three recurrent neural architectures inspired by the proprioceptive system found in mammals; Exo-sensing, Ego-sensing, and Composite. Through the use of Particle Swarm Optimisation the robot controllers are adapted to perform the task of identifying motion dynamics within their environment. We highlight the effect of sensory-motor coordination on the performance in the task when applied to each of the three neural architectures.

References

  1. McKibbin, S.P., Amavasai, B., Selvan, A.N., Caparrelli, F., Othman, W.A.F.W, 2007. Recurrent Neural Robot Controllers: Feedback Mechanisms for identifying Environmental Motion Dynamics. Submitted.
  2. Clerc, M., 1999. The swarm and the queen: towards a deterministic and adaptive particle swarm optimization. In Proceedings of the 1999 ICEC, Washington DC, pp1951-1957.
  3. Clerc, M., Kennedy, J., 2002. The particle swarm - explosion, stability, and convergence in amultidimensional complex space. In IEEE Transactions on Evolutionary Computation, vol. 6, issue 1.
  4. Eberhart, R.C. Shi, Y., 2000. Comparing inertia weights and constriction factors in particleswarm optimization. In Proceedings of the 2000 Congress on Evolutionary Computation.
  5. Kennedy, J., Eberhart, R.C., 1995. Particle Swarm Optimisation. In Proceedings of the IEEE Int. Conf. Neural Networks.
  6. Nolfi, S., 2002a. Evolving robots able to self-localize in the environment: The importance of viewing cognition as the result of processes occurring at different time scales. In Connection Science, vol. 14 issue 3.
  7. Nolfi, S., Marocco D., 2002b. Active perception: A sensorimotor account of object categorization. In From Animals to Animats. In B. Hallam, D. Floreano, J. Hallam, G. Hayes, J-A. Meyer (eds.) Proceedings of the VII International Conference on Simulation of Adaptive Behavior. Cambridge, MA: MIT Press, pp. 266-271.
  8. O'Regan, J. K., Noe, A., 2001. A sensorimotor account of vision and visual consciousness. In Behavioral and Brain Sciences, 24(5):939-73.
Download


Paper Citation


in Harvard Style

Paul McKibbin S., Amavasai B., N. Selvan A., Caparrelli F. and A. F. W. Othman W. (2008). THE ROLE OF SENSORY-MOTOR COORDINATION - Identifying Environmental Motion Dynamics with Dynamic Neural Networks . In Proceedings of the Fifth International Conference on Informatics in Control, Automation and Robotics - Volume 4: ICINCO, ISBN 978-989-8111-31-9, pages 129-136. DOI: 10.5220/0001495101290136


in Bibtex Style

@conference{icinco08,
author={Stephen Paul McKibbin and Bala Amavasai and Arul N. Selvan and Fabio Caparrelli and W. A. F. W. Othman},
title={THE ROLE OF SENSORY-MOTOR COORDINATION - Identifying Environmental Motion Dynamics with Dynamic Neural Networks},
booktitle={Proceedings of the Fifth International Conference on Informatics in Control, Automation and Robotics - Volume 4: ICINCO,},
year={2008},
pages={129-136},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001495101290136},
isbn={978-989-8111-31-9},
}


in EndNote Style

TY - CONF
JO - Proceedings of the Fifth International Conference on Informatics in Control, Automation and Robotics - Volume 4: ICINCO,
TI - THE ROLE OF SENSORY-MOTOR COORDINATION - Identifying Environmental Motion Dynamics with Dynamic Neural Networks
SN - 978-989-8111-31-9
AU - Paul McKibbin S.
AU - Amavasai B.
AU - N. Selvan A.
AU - Caparrelli F.
AU - A. F. W. Othman W.
PY - 2008
SP - 129
EP - 136
DO - 10.5220/0001495101290136