Model-based vision for robotic manipulation of twisted tubular parts: using affine transforms and heuristic search

We discuss the model-acquisition and model-matching aspects of a model-based vision system for the bin-picking of twisted tubular parts. The system uses both 3-D structured-light vision and 2-D binary vision in a synergistic manner. Binary vision kicks in when the robot picks up a tube using a graspable fragment identified as such by the 3-D vision system; the tube thus picked up is placed on a backlit table so that its pose can be calculated from its 2D image with sufficient precision to allow its assembly with another object. The binary vision carries out pose calculation by affine matching the projected image with a small set of model projections, each corresponding to a separate stable pose of the object on a flat surface and each represented by the coordinates of only four points. This paper presents a heuristic algorithm for determining the placement of the four points for representing the model projections