Abstract
An architecture for a motor control system inspired by biological organisms is outlined. The core of this architecture is a model of the direct kinematics of the articulated chain (AC) under control. The advantage of using the direct kinematics solution to solve the inverse kinematics problem is that the former is separable and can be broken down to low-dimensional problems. A novel algorithm to adaptively learn, in a hierarchical fashion, the direct kinematics solution of an AC with many degrees of freedom (DoF) is presented. The algorithm is designed such that only neurally implementable operations or functions are used. The algorithm is shown to work with an articulated chain with nine DoF. On average, less than 200 iterations per joint are required.
Supported by grants from the DFG (GK KOGNET) and the German Federal Ministry for Science and Technology (01 IN 504 E9).
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© 1996 Springer-Verlag Berlin Heidelberg
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Zadel, S. (1996). An algorithm for bootstrapping the core of a biologically inspired motor control system. 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_107
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DOI: https://doi.org/10.1007/3-540-61510-5_107
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