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Robotic De-palletizing Using Uncalibrated Vision and 3D Laser-Assisted Image Analysis

机译:使用未校配视觉和3D激光辅助图像分析的机器人去托。

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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 differenting 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.
机译:在造纸厂行业中,袋子堆叠和无堆叠是非常劳动密集型的工作。公司很难找到足够的人填补这些职位。此外,重复堆栈和未堆叠工作很容易导致腰部伤害。因此,机器人脱托码化系统是非常理想的。可靠且鲁棒地引导机器人工具插入袋堆上的间隙,以拾取一层袋,而不会扰乱堆叠由于间隙中心位置和间隙尺寸根据不同的速度而取决于不同的空间在它上方的层,所谓的“变形紧缩”因子。在本文中,开发了基于相机空间操纵(CSM)的未校准视觉和3D激光辅助图像分析的方法。开发的原型系统显示了去托盘化过程中可靠的间隙插入。它已准备好安装在Smurfit-Stone Container Corporation的工厂。

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