Abstract
In this article we report how Dynamic Cell Structures (DCS) [1] can be utilized to learn fast and accurate saccade control of a four-degrees-of-freedom Binocular Head. We solve the order selection problem by incremental growing of a DCS network until the controller meets a pre-specified precision. Calculation of the controller output is very fast and suitable for realtime control since the resulting network is as small as possible and only the best matching unit and its topological neighbors are activated on presentation of an input stimulus. Training of the DCS is based on error feedback learning and proceeds in two phases. In the first phase we use a crude model of the cameras and the kinematics of the head to learn the topology of the input submanifold and a rough approximation off-line. In a second phase, the operating phase, we employ error feedback learning for online adaptation of the linear output units. Besides our TRC binocular head we use a Datacube image processing system and a Stäubli R90 robot arm for automated training in the second phase. The controller is demonstrated to successfully correct errors in the model and to rapidly adapt to changing parameters.
Preview
Unable to display preview. Download preview PDF.
References
J. Bruske and G. Sommer: Dynamic Cell Structure learns Perfectly Topology Preserving Map, Neural Computation, Vol. 7, No. 4 (1995) 845–865
P. Dean, J.E. Mayhew, N. Thacker and P.M. Langdon: Saccade control in a simulated robot camera-head system: neural net architectures for efficient learning of inverse kinematics, Biol. Cybern., Vol. 66 (1991) 27–36
B. Fritzke: Growing cell structures — a self-organizing network for unsupervised and supervised learning, Neural Networks, Vol. 7, No. 9 (1995) 1441–1460
M. Kawato: Feedback-error-learning neural network for supervised motor learning, In: Advanced Neural Computers, Elsevier, Amsterdam (1990) 365–372
J.E. Mayhew, Y. Zheng and S. Cornell: The adaptive control of a four-degrees-of-freedom stereo camera head, Phil. Trans. R. Soc. Lond., Vol. 337 (1992) 315–326
Thomas Martinetz and Klaus Schulten: Topology Representing Networks, Neural Networks, Vol 7 (1994) 505–522
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 1996 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Brüske, J., Hansen, M., Riehn, L., Sommer, G. (1996). Adaptive saccade control of a Binocular Head with Dynamic Cell Structures. In: von der Malsburg, C., von Seelen, W., Vorbrüggen, J.C., Sendhoff, B. (eds) Artificial Neural Networks — ICANN 96. ICANN 1996. Lecture Notes in Computer Science, vol 1112. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-61510-5_39
Download citation
DOI: https://doi.org/10.1007/3-540-61510-5_39
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-61510-1
Online ISBN: 978-3-540-68684-2
eBook Packages: Springer Book Archive