Automated Scanning Techniques Using UR5 - Homar Lopez-Hawa; Alexander VanPelt; Suveen Emmanuel; Yimesker Yihun (Journal of Robotics)
This study seeks to advance technologies pertaining to integration of low-cost collaborative robots to perform scanning operations where moderate accuracy is needed. Part inspection is an almost universal aspect of manufacturing which traditionally requires human observation. Advanced metrology techniques, such as scanning, allow greater inspection capabilities but still require a human operator and require significant capital investment. Using off-the-shelf line scanners in conjunction with small collaborative robots can completely automate the inspection process while minimizing cost. This project seeks to investigate the feasibility of utilizing a UR5 robot with a Keyence line scanner for scanning inspection in an industrial setting. Data from the line scanner is gathered, along with the position and orientation of the end-effector of the robot. The data are collected, combined, and analyzed in MATLAB to generate surface geometry. A user interface will allow viewing of the specific points gathered, expedite product inspection during manufacturing, and involve humans in higher skill-based decision-making tasks. A professional grade scan of the test part is used for comparison of experimentally gathered data. Feasibility is assessed on cost, effectiveness, ease of programming and operation, and development difficulty. In the preliminary result, it was found that the UR5 and line scanner provide a cheap and easily programmable and automated solution to line inspection. However, effectiveness and difficulty of development may pose challenges that require future research.