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Machine Learning based Pallets Detection and Tracking in AGVs (2004.08965v1)
Published 19 Apr 2020 in cs.CV, cs.LG, cs.SY, eess.IV, and eess.SY
Abstract: The use of automated guided vehicles (AGVs) has played a pivotal role in manufacturing and distribution operations, providing reliable and efficient product handling. In this project, we constructed a deep learning-based pallets detection and tracking architecture for pallets detection and position tracking. By using data preprocessing and augmentation techniques and experiment with hyperparameter tuning, we achieved the result with 25% reduction of error rate, 28.5% reduction of false negative rate, and 20% reduction of training time.