Abstract
Structure and function of a small but effective neural network controlling the behavior of an autonomous miniatur robot is analyzed. The controller was developed with the help of an evolutionary algorithm, and it uses recurrent connectivity structure allowing non-trivial dynamical effects. The interplay of three different hysteresis elements leading to a skilled behavior of the robot in challenging environments is explicitly discussed. © Springer-Verlag Berlin Heidelberg 2002.
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CITATION STYLE
Hülse, M., & Pasemann, F. (2002). Dynamical neural schmitt trigger for robot control. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 2415 LNCS, pp. 783–788). Springer Verlag. https://doi.org/10.1007/3-540-46084-5_127
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