Abstract
In the industrial production line, putting several small packages into large packages with the required arrangement rules still requires a lot of manual work to complete. In order to solve this problem, we build an automatic robot gras** system based on robotic arm, industrial camera and a uniform-speed conveyor, which can automatically put small packages into large packages. We use the YOLO algorithm to identify the position, category and number of small packages. The number of snacks identified is utilized to plan the degree of gripper closure. The trajectory of the small packages can be predicted according to the speed of the conveyor and the position of small packages on the robot coordinate system, then we fuse multiple predicted trajectories to form a complete and coherent robot arm trajectory to grasp the small packages and put them into large packages. This system can save a large amount of labor and reflect the intelligence of the robot.
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Acknowledgement
The work was jointly supported by Bei**g Natural Science Foundation (4212933), Scientific Research Project of Bei**g Educational Committee (KM202110005023) and National Natural Science Foundation of China (62273012, 62003010).
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Liu, C., Fang, J., Yu, P. (2023). Automatic Packaging System Based on Machine Vision. In: Sun, F., Cangelosi, A., Zhang, J., Yu, Y., Liu, H., Fang, B. (eds) Cognitive Systems and Information Processing. ICCSIP 2022. Communications in Computer and Information Science, vol 1787. Springer, Singapore. https://doi.org/10.1007/978-981-99-0617-8_16
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DOI: https://doi.org/10.1007/978-981-99-0617-8_16
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