<b>Electric Vehicle Charging Port Rec</b><b>ognition and Positioning Algorithm Based on Point Cloud（ID:</b><b>PONE-D-24-13766R</b><b>1</b><b>）</b>

This study introduces an automatic identification and positioning method for electric vehicle charging ports based on 3D point cloud key-point features. Compared to traditional image processing and deep learning methods, which often entail dealing with large data sets and computational complexity, this approach demonstrates superior accuracy and robustness in the application of charging robots.本研究提出了一种基于3D点云（3D point cloud）关键点特征的电动汽车充电口自动识别与定位方法。相较于传统图像处理与深度学习方法通常需要处理大规模数据集且计算复杂度较高的局限，该方法在充电机器人应用场景中展现出更优异的精度与鲁棒性。