Fast detection method for Baggage pallet based on multi-layer

分类： 计算机科学 >> 计算机应用技术 提交时间： 2022-04-18

Qijun Luo Zheng Li Qingji Gao

摘要： In the self-service baggage check and sorting of civil aviation, it is an essential function to automatically detect whether pallets is added to the self-dropped baggage, but the pallets are largely obscured by the embedded baggage,whichbecomes a challenging problem.For this issue, a fast detection method for embedded baggagepallets based on multi-layer skeleton model registrationis proposed. In order to describe the characteristics of the pallet, the point cloud skeleton model and the point-line model are constructed by the 3D point cloud model. During online detection, the designed banded feature description and extraction method is used to grab the border point cloud, and the proposed point-line potential energy iterative algorithm is used to registration the point-line model and horizontal border points. Then, point cloud iterative nearest point registration based on random sampling consistency is used to achieve accurate registration and pose calculation.As a result, the possibility of the existence of the palletis judged. The effectiveness of the algorithm is verified by a variety of actual pallet detection experiments. A variety of typical comparative experimental results show that when the palletpoint cloud is missing within 70%, the algorithm can still maintain the accuracy of 94%and the speed exceeds typical algorithm is more than 6 times.

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