Abstract
This paper is about automatically guided vehicle (AGV) system in the automated-storage-and-retrieval-system (ASRS). In ASRS, it usually uses AGV system to transport materials, because it not only efficient but can cost down logistic cost. However, the major problem of the application about AGV is how to find the position of the pallets due to the difficulties to locating the pallet position on a complicated factory environment. In this work, Haar like-based Adaboost scheme with adaptive structure feature of pallets algorithm to detect pallets is presented, and by combining direction weighted overlapping (DWO) ratio, it can avoid those non-optimal candidates in object tracking. The experimental result shows this method can remove most of the non-stationary background and can increase the average pallet detection rate by 95%.
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http://tutorial-haartraining.googlecode.com/svn/trunk/data/negatives/.
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Syu, JL., Li, HT., Chiang, JS., Hsia, CH., Wu, PH., Hsieh, CF. (2018). An Assisted Forklift Pallet Detection with Adaptive Structure Feature Algorithm for Automated Storage and Retrieval Systems. In: Yen, N., Hung, J. (eds) Frontier Computing. FC 2016. Lecture Notes in Electrical Engineering, vol 422. Springer, Singapore. https://doi.org/10.1007/978-981-10-3187-8_26
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DOI: https://doi.org/10.1007/978-981-10-3187-8_26
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