TINA: A 3D Vision System for Pick and Place

Abstract

Abstract The paper describes the Sheffield AIVRU 3D vision system for robotics. The system currently supports model-based object recognition and location; its potential for robotics applications is demonstrated by its guidance of a UMI robot arm in a pick-and-place task. The system comprises: recovery of a sparse depth map using edgebased passive stereo triangulation; grouping, description and segmentation of edge segments to recover a 3D description of the scene geometry in terms of straight lines and circular arcs; statistical combination of 3D descriptions for the purpose of object model creation from multiple stereo views, and the propagation of constraints for within-view refinement; and matching 3D wireframe models to 3D scene descriptions to recover an initial estimate of their position and orientation.