A unique sensor fusion system for coordinate measuring machine tasks

This paper describes a real-time hierarchical system that fuses data from vision and touch sensors to improve the performance of a coordinate measuring machine (CMM) used for dimensional inspection tasks. The system consists of sensory processing, world modeling, and task decomposition modules. It uses the strengths of each sensor-the precision of the CMM scales and the analog touch probe and the global information provided by the low resolution camera-to improve the speed and flexibility of the inspection task. In the experiment described, the vision module performs all computations in image coordinate space. The part's boundaries' are extracted during an initialization process and then the probe's position is continuously updated as it scans and measures the part surface. The system fuses the estimated probe velocity and distance to the part boundary in image coordinates with the estimated velocity and probe position provided by the CMM controller. The fused information provides feedback to the motion controller as it guides the touch probe to scan the part. We also discuss integrating information from the vision system and the probe to autonomously collect data for 2-D to 3-D calibration, and work to register Computer Aided Design (CAD) models with images of parts in the workplace.