Robotic de-palletizing using uncalibrated vision and 3D laser-assisted image analysis

In the paper-container industry, bag stacking and un-stacking are very labor-intensive work. It is hard for companies to find enough people to fill these positions. Also the repetitive stack and un-stack work can easily cause back and waist injury. Therefore robot de-palletizing system is highly desirable. Guiding a robot tool reliably and robustly to insert into the gap on bag stack to pick up a layer of bags without disturbing the stack is highly challenging due to the variation of the gap-center position and gap size under different pressure depending upon the number of layers above it, the so-called ¿variable crunch¿ factor. In this paper, the method combining an uncalibrated vision and 3D laser-assisted image analysis based on camera-space manipulation (CSM) is developed. The developed prototype system demonstrates the reliable gap insertion in de-palletizing process. It is ready to be installed to a factory floor at the Smurfit-Stone Container Corporation.