论文标题
AGV中的基于机器学习的托盘检测和跟踪
Machine Learning based Pallets Detection and Tracking in AGVs
论文作者
论文摘要
自动导向车辆（AGV）的使用在制造和分销操作中发挥了关键作用，提供了可靠，有效的产品处理。在这个项目中，我们为托盘检测和位置跟踪构建了一个基于学习的托盘检测和跟踪体系结构。通过使用数据预处理和增强技术以及实验超参数调整，我们通过降低错误率降低25％，降低了虚假负率和降低20％的训练时间，实现了结果。
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.
