Based on AI visual large models, it can accurately identify cookies of any shape, suitable for production scenarios such as fast packaging on assembly lines, tray loading, boxing, and feeding into packaging machines.

Based on AI visual large models, it accurately identifies stacked materials for quick picking and sorting, suitable for production scenarios such as fast assembly line boxing, palletizing, cartoning, and feeding into packaging machines.

Based on an AI visual large model, cookies are sorted and palletized by quickly locating and classifying them according to features such as shape, enabling fast palletizing and boxing of cookies. It is suitable for production scenarios such as fast-line boxing, palletizing, case packing, and feeding blocks into packaging machines.

Based on AI visual large models, it can sort and stack youtiao (Chinese fried dough sticks). It can quickly locate and classify according to features such as color and shape, achieving precise sorting, rapid stacking, and packaging to meet production needs. It is suitable for production scenarios such as fast boxing, palletizing, packing, and feeding into block machines on assembly lines.

The Yujunsheng Chocolate Intelligent Boxing Line can automatically organize the bottoms and lids of chocolate packaging boxes, automatically pick up trays and insert them into the box bottoms, automatically place chocolates into the trays already placed in the box bottoms, and automatically close the lids onto the boxes containing chocolate. This production line can be divided into five modules: 1. Chocolate loading module; 2. Lid closing module; 3. Automatic tray picking and insertion module; 4. Box bottom organization module; 5. Box lid organization module. The Yujunsheng automatic boxing line uses a collaborative operation mode integrating DELTA robots, vision inspection equipment, SCARA manipulators, and AI intelligent algorithms. It features high speed, excellent precision, strong stability, and flexibility. The entire line is independently developed and designed, supports fine-tunable modular non-standard customization, and provides personalized flexible packaging solutions, making it widely applicable in the food, bakery, pharmaceutical, and daily chemical industries.

Based on AI visual large models, various materials can be sorted by quickly locating and classifying them according to features such as color, text, and shape. It is suitable for irregularly shaped and transparent materials, and can be rapidly trained and applied to complex materials for multifunctional sorting, palletizing, boxing, and packaging production lines.