Affiliation:
1. Department of Mechanical Engineering, The Ohio State University, Columbus, OH 43210-1154
Abstract
Multiple-sensor integration of vision and touch probe sensors has been shown to be a feasible approach for rapid and high-precision coordinate acquisition [Shen, T. S., Huang, J., and Meng, C. H., 2000, “Multiple-sensor integration for rapid and high-precision coordinate metrology,” IEEE/ASME Trans. Mechatron. 5, pp. 110–121]. However, the automation of coordinate measurements is still hindered by unknown surface areas that cannot be digitized using the vision system due to occlusions. It is identified that the estimation and reasoning of unknown surface areas, and automatic sensor planning using multiple sensors are two key issues. In order to advance multiple-sensor integration technologies toward a fully automatic and agile coordinate metrology, information integration algorithms for estimating and reasoning unknown surface areas, and an automatic multiple-sensor planning environment are developed in this paper. Experimental and simulation results are also demonstrated.
Subject
Industrial and Manufacturing Engineering,Computer Graphics and Computer-Aided Design,Computer Science Applications,Software
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