Machining Accuracy Improvement Through Visual Control of an Active Display

The objective of this research is to formulate a physics-based predictive model relating achievable resolution of a new class of positioning system to a limited set of design parameters. The manufacturing lab at the Clemson University International Center for Automotive Research (CU-ICAR) has developed a new type of position sensing method using computer vision instead of optical position sensor. This new method is potentially to be implemented to a two dimensional motion control devices such as a CNC milling machine to provide better accuracy and high quality product, but is subject to fundamental control and image processing barriers. Thus, the goal of this project is to model the spatial resolution for this new class of position measurement system, and to explore the predictive efficacy of the model for spatial positioning. It is anticipated that sensing of a controllable array of pixel elements will allow high-precision motion control of simultaneous-axis positioning without need for error mapping and inversion. The prototype system is tested on a two-axis positioning stage for simultaneous axis closed-loop motion control.

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