Object recognition and localization using optical proximity sensor system: polyhedral case

The authors present an algorithm for the recognition and localization of 3D polyhedral objects based on an optical proximity sensor system. In particular, the representation of a polyhedral object and the determination of the optimal sensor trajectory for the next probing are considered. The object representation is based on two levels of hierarchy: the description of a 3D structure by an intersurface relation description table (SDT) and the surface normal vector (SNV) distribution graph, and the description of individual surfaces by interedge relation description tables (EDTs). The partially filled SDT and EDTs of the test object are matched against the SDT and EDTs of a model object to extract all the possible interpretations. In order to achieve the maximum discrimination among all possible interpretations, the optimal sensor trajectory for the next probing is determined as follows: (1) select the optimal beam orientation on the basis of the SNV distribution graph of the multiple interpretation image (MII), where the MII is formed with reference to the hand frame by localizing the test object on the basis of individual interpretations, and (2) determine the optimal probing plane by projecting the MII onto the projection plane perpendicular to the beam orientation and deriving the optimal path on the probing plane. Simulation results are shown