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Normal Direction Measurement and Optimization With a Dense Three-Dimensional Point Cloud in Robotic Drilling

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In large-scale structure assembly, the normal direction of a drilled surface is required to be measured online instead of extracted directly from the computer-aided design model because of tool error,… Click to show full abstract

In large-scale structure assembly, the normal direction of a drilled surface is required to be measured online instead of extracted directly from the computer-aided design model because of tool error, cutting force, and other factors. To this end, first, a high-resolution structured-light-based three-dimensional (3-D) measurement is adopted to improve measurement reliability; second, tensor voting is proposed to remove noise and fill in blanks in the measured 3-D point cloud to obtain a uniform point distribution for surface fitting; and third, the surface smoothness after rivet installation is defined and optimized. The proposed methods are verified by simulations and experiments. The results show that the proposed methods are effective.

Keywords: three dimensional; measurement; point; point cloud; normal direction

Journal Title: IEEE/ASME Transactions on Mechatronics
Year Published: 2018

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