Training an Animated Arm to Reach for Objects in Space Using Neural Networks

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University of California, Santa Cruz, 1989 - Robots - 136 pages
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In order to analyze the feasibility of using neural networks for automatic motion control, the simple motion of an arm reaching for an object in a two dimensional world was used. Initially, a multi-layered feed-forward network was trained to predict the position of an arm at the following time frame, given only the position of the arm at the current time frame and its relative position from the object. After the network was trained using the back-propagation learning algorithm, the performance of the network was tested, producing an animated motion that was far from acceptable, even though the network's training performance leveled off to a low mean error. It was also discovered that a highly acceptable animated motion could be produced when the network continued to be trained during the testing phase.

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Contents

Introduction
1
Experimental Methods
21
The Initial Experiments
30

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