Adaptive datum generation for automatic dimensional measurement

Adaptive datum generation for automatic dimensional measurement
Title:
Adaptive datum generation for automatic dimensional measurement
Other Titles:
5th International Conference on Robotics and Artificial Intelligence (ICRAI)
DOI:
Publication URL:
Publication Date:
24 November 2019
Citation:
Abstract:
Dimensional measurement is critical for quality control. Manual dimensional measurement using standard gauges can only be applied on a few datums. To measure a huge number of datums, a component needs to be scanned into a point cloud and measured digitally. For precision components, datum generation on the scanned point cloud is labor-intensive. Given a raw point cloud from scanner, this paper proposes an automatic dimensional measurement solution with an adaptive local registration algorithm and an adaptive datum generation algorithm. Using datums on the CAD model as reference, the adaptive local registration algorithm selects local regions on the scanned model to compensate the local deviation between the CAD model and the scanned model. After that, with outliers and noises in the raw data, the adaptive datum generation algorithm creates the correct datums on the scanned model adaptive to the actual geometry. Dimensional measurement based on the generated datums can be achieved automatically. Moreover, the solution does not require users to manually preprocess the point cloud, such as outlier and noise removal. As such, it improves the productivity in dimensional inspection.
License type:
PublisherCopyrights
Funding Info:
Description:
ISBN:

Files uploaded:
File Size Format Action
There are no attached files.