Positioning of Flexible Boom Structure Using Neural Networks

Authors:
Jarno Mielikäinen;Ilkka Koskinen;Heikki Handroos;Pekka Toivanen;Heikki Kälviäinen
Affiliations:
-;-;-;-;-
Venue:
CAIP '01 Proceedings of the 9th International Conference on Computer Analysis of Images and Patterns
Year:
2001

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Abstract

Deflection compensation of flexible boom structures in robot positioning is becoming an important part of machine automation. Positioning is usually done using tables containing the magnitude of the deflection with inverse kinematics solutions of a rigid manipulator. In this paper, a method for locating the tip of a flexible manipulator using machine vision and a method for positioning the tip of a flexible manipulator using neural networks are proposed. A machine vision system was used in the data collection phase to locate the boom tip and the collected data was used to train MLP-networks. The developed methods improve the accuracy of manipulator positioning, and it can be integrated in the control system of the manipulator. The methods have been tested in real-time laboratory environment, and the results were promising. During the testing, the locating and the positioning were noticed to function as required, yielding reliable results with sufficient computation times.