A Variational Approach to Constructivist Learning for Mobile Robot Navigation
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Author(s)
Mehta, Tejas R.
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Abstract
In this paper, we present a constructivist approach
for the Learning by Example problem, where control laws (or behaviors) are learned in order to approximate a training
trajectory. The new behaviors are learned by systematically
improving upon existing capabilities. Within this context, the learning problem is formulated as an optimal control problem,
and variational arguments are used to obtain optimality
conditions. Numerical algorithms that utilize the optimality
conditions to attain a stationary solution are produced. A small-scale
navigation example is discussed in order to highlight the
operation of the proposed approach.
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Date
2007-12
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Text
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Proceedings