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Combining force and position measurements for the monitoring of robotic assembly

Geir Hovland, B.J. McCarragher

Year
2002
Citations
19

Abstract

A method for combining dynamic force and static position measurements for the monitoring of assembly is presented. A multilayer perceptron (MLP) network is used as a classifier where the individual network outputs correspond to contact state transitions occuring during the assembly process. When a contact state transition occurs, the MLP output with the largest value is chosen. The recognised contact state is sent to a discrete event controller which guides the workpiece through a series of contact states to the final desired configuration. The MLP has been successfully implemented on a Motorola 68040 based VxWorks board with successful recognition rates of 94.4% and 92.0% on a training set and an independent test set, respectively.

Keywords

Multilayer perceptronPosition (finance)Computer scienceContact forceClassifier (UML)Test setArtificial neural networkState (computer science)Artificial intelligenceControl theory (sociology)

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