Abstract: A method of controlling a robot system includes the steps of providing a tool supported by a moveable mechanism of the robot system, providing a workpiece supported by a holder, generating an image of the workpiece, extracting a data from the image, the data relating to a feature of the workpiece, generating a continuous three-dimensional path along the workpiece using data extracted from the image, and moving the tool along the path.

Abstract: A method of controlling a robot system includes the steps of providing a tool supported by a moveable mechanism of the robot system, providing a workpiece supported by a holder, generating an image of the workpiece, extracting a data from the image, the data relating to a feature of the workpiece, generating a continuous three-dimensional path along the workpiece using data extracted from the image, and moving the tool along the path.

Abstract: A method and system for automatically determining the position and orientation of an object by utilizing as few as a single digital image generated by as few as a single camera without the use of a structured light. The digital image contains at least three non-colinear geometric features of the object. The three features may be either coplanar or non-coplanar. The features or targets are viewed such that perspective information is present in the digital image. In a single camera system the geometric features are points, and in a multi-camera system, the features are typically combinations of points and lines. The location of the features are determined and processed within a programmed computer together with reference data and camera calibration data to provide at least three non-parallel 3-D lines. The 3-D lines are utilized by an iterative algorithm to obtain data relating to the position and orientation of the object in 3-D space.

Abstract: A method and system are provided for automatically locating an object at a vision station by performing an edge-detecting algorithm on at least a portion of the gray-scale digitized image of the object. Preferably, the algorithm comprises an implementation of the Hough transform which includes the iterative application of a direction-sensitive, edge-detecting convolution to the digital image. Each convolution is applied with a different convolution mask or filter, each of which is calculated to give maximum response to an edge of the object in a different direction. The method and system have the ability to extract edges from low contrast images. Also, preferably, a systolic array processor applies the convolutions.