Multi-stage neural networks with application to motion planning of a mechanical snake

Date
2003-06
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Source Title
Proceedings of the American Control Conference, 2003
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Publisher
IEEE
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Pages
1278 - 1283
Language
English
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Abstract

An efficient approach to nonlinear control problems in which the plant is to be driven to a desired state using a neural network controller in a number of steps is by representing the whole process as a multi - stage neural network. In this paper, an explicit formulation of the back propagation algorithm is developed for such networks. Later, this approach is used to build up a path planner for a mechanical snake (a robot composed of a sequence of articulated links). This path planner, together with a tracking algorithm, is shown to get the mechanical snake out of a collision-free closed region.

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