Object Reconstruction and Extraction for a Visually Guided Robot System

S. Chang, J. Fuller, and A. Farsaie (USA)


Surface reconstruction, object modeling, 3D object extraction, surface modeling, visually guided robot


For visual guided robot systems, there are two main approaches for locating the objects and scene, the position-based approach and the image-based approach. Object modeling and recognition are the major challenges to both approaches. In this paper, we propose a method that models and recognizes objects using a position-based approach and that detects obstacles using an image-based approach. Operational objects and static obstacle objects are modeled by the position-based approach and, moving obstacle objects are detected by the image-based approach.

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