激光与光电子学进展, 2019, 56 (10): 101203, 网络出版: 2019-07-04
基于SURF算法的自动导引车精确定位技术 下载: 1084次
Precise Positioning Technology for Automatic Guided Vehicles Based on SURF Algorithm
测量 自动导引车 视觉导引 二维码 精确定位 measurement automated guided vehicle visual navigation quick response code precise positioning
摘要
提出了一种基于加速稳健特征(SURF)算法的精确定位的方法,通过识别地面铺设的二维(QR)码完成了定位预判与姿态矫正。对获取的QR图像进行预处理,并采用SURF算法提取图像中的特征点信息,匹配实时图像与目标图像的特征点,并利用最小二乘拟合获取图像间的转换矩阵,将转换矩阵与自动导引车(AGV)的视觉导引模型结合以实现AGV的精确定位。实验结果表明,在结构尺寸较大的重载AGV中,所提算法的定位稳健性较好,精度达到±1 mm。
Abstract
A precise positioning technique is proposed based on the speeded up robust features (SURF) algorithm. By identifying the quick response (QR) code laid on the ground, this technique is used to complete positioning prediction and attitude correction. First, the acquired QR image is preprocessed, and the feature point information of the image is extracted by the SURF algorithm. The feature points of both the real-time image and the target image are then matched, and the transformation matrix between these two images is obtained by least square fitting. Finally, the transformation matrix is combined with the visual guidance model of the automatic guided vehicle (AGV), and the precise positioning of the AGV is realized. The experimental results show that for a heavy-duty AGV with a large structural size, the proposed method has robust positioning with a precision of ±1 mm.
高雪松, 李宇昊, 张立强, 陈志华. 基于SURF算法的自动导引车精确定位技术[J]. 激光与光电子学进展, 2019, 56(10): 101203. Xuesong Gao, Yuhao Li, Liqiang Zhang, Zhihua Chen. Precise Positioning Technology for Automatic Guided Vehicles Based on SURF Algorithm[J]. Laser & Optoelectronics Progress, 2019, 56(10): 101203.