Intelligent Robotic Palletizer System
Jeng-Dao Lee, Chen-Huan Chang, En-Shuo Cheng, Chia-Chen Kuo, Chia-Ying Hsieh
Abstract
In the global wave of automation, logistics and manufacturing are indispensable and important industries. Among them, the related automatic warehousing system is even more urgently needed. There are quite a few cases of using robotic arms in the current industry cargo stacking operations. Traditional operations require engineers to plan the stacking path for the robotic arm. If the size of the object changes, it will take extra time to re-plan the work path. Therefore, in recent years, quite a lot of automatic palletizing software has been developed; however, none of it has a detection mechanism for stacking correctness and personnel safety. As a result, in this research, an intelligent robotic palletizer system is developed based on a self-developed symmetrical algorithm to stack the goods in a staggered arrangement to ensure the overall structure. Innovatively, it is proposed to check the arrangement status and warnings during the visual stack inspection to ensure the correctness of the stacking process. Besides, an AI algorithm is imported to ensure that personnel cannot enter the set dangerous area during the work of the robotic arm to improve safety during stacking. In addition to uploading the relevant data to the cloud database in real time, the stacking process combined database and vision system also provide users with real-time monitoring of system information.