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High-precision visual localization based on an improved shape-based matching algorithm

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Abstract

To deal with the requirement of high-precision localization of large-size workpieces in an industrial environment, an improved shape-based matching algorithm is proposed based on the phase stretching transformation and the iterative closest point algorithms. Basler industrial cameras are used to collect images of large-size workpieces, such as glass. The experimental results show that the average localization error is $0.05\,{\pm}\,0.013\,\,{\rm mm}$, which can meet the requirements of practical applications. This algorithm can effectively and accurately achieve high-precision localization of different positions of multi-directionally transformed objects in industrial environments.

© 2021 Optical Society of America

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