, Associate Professor, UMD-Industrial Engineering
Repainting existing roadway markings (turn arrows, STOP messages, railroad crossings, etc.) is an important maintenance task. The Minnesota Department of Transportation estimates that more than 75 percent of symbol and message painting is repainting existing markings. It would be extremely valuable if an automated painting system possessed a vision guidance capability to repaint an existing mark accurately with little operator input. In this project a vision system was developed that is capable of identifying existing painted pavement markings and determining their dimensions, location, and orientation. Techniques were also developed whereby this information could be used to determine the location of the marking in the workspace of a painting robot to enable it to accurately repaint the marking. The vehicle-mounted robotic painter is still being built and tested, so final test results will not be available until the vision system can be completely integrated with the painter and the two can be tested together. The accuracy of the projection produced using the techniques developed in this project would suggest that the final system will be capable of repainting pavement markings almost exactly where they appear on the roadway. Expected benefits of the deployment of a vision-guided robotic painting device include improved operator safety, improved productivity, and improved flexibility in roadway marking and repainting operations. Potential users of this technology are city, county, state, and federal government agencies and private companies or contractors.