Object recognition and pose estimation with a fast and versatile 3D robot sensor

Abstract

Presents a new approach to object recognition and pose estimation based on a 3D robot sensor, which produces range images of a scene along problem specific lines of sight. Recognition is realized as a hypothesis generation/hypothesis verification process. Hypothesis generation is based on a minimal number of predominant and connected object parts in one or more range images determining all 6 degrees of freedom of an objects pose. This set of object parts is transformed into a hypotheses set by simple look-up operations in precalculated hash tables. In the subsequent verification step the authors determine an inspection list for the best recognizable, most distinctive and best visible object parts in this hypotheses set and verify the hypotheses by searching these object parts in existing or new range images.<>