Robot path generation for surface processing applications via neural networks

Pasi Koikkalainen; Markus Varsta

doi:10.1117/12.256279

29 October 1996 Robot path generation for surface processing applications via neural networks

Pasi Koikkalainen, Markus Varsta

Proceedings Volume 2904, Intelligent Robots and Computer Vision XV: Algorithms, Techniques,Active Vision, and Materials Handling; (1996) https://doi.org/10.1117/12.256279
Event: Photonics East '96, 1996, Boston, MA, United States

Abstract

This paper presents a hierarchical method, based on a deterministic variant of the self-organizing map, that provides an elegant solution for automated surface processing, e.g. for robot painting and sand-blasting. Given a set of data points in arbitrary order from the object surface, the proposed method is able to generate a path, where the robot hand position and its direction are optimized using separate criteria, and the tool path is smooth and covers the object uniformly. Input data may come from a laser measurement system, CAD model, digital camera, or from human assisted object digitizing system. The algorithm is reliable and easy to implement, and a good alternative for costly manual training of a robot.

Citation Download Citation

Pasi Koikkalainen and Markus Varsta "Robot path generation for surface processing applications via neural networks", Proc. SPIE 2904, Intelligent Robots and Computer Vision XV: Algorithms, Techniques,Active Vision, and Materials Handling, (29 October 1996); https://doi.org/10.1117/12.256279

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