Abstract
Intelligent image processing blurs the distinction between Guidance Vision for Robots (GVR) and Automated Visual Inspection (AVI) applications. The paper presents AI techniques for interactive learning of scene-object models by feature descriptions of part flows. Robot grippers are modelled by fingerprints for ***collision-free part access. The parameters of the vision models are remotely created by a Server application which accepts simultaneous connections over LAN/Internet with multiple Clients – executing on IBM PC robot terminals integrated in flexible, networked manufacturing structures. Experimental results are reported for cluster and pattern construction for part recognition.
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