多目视觉与激光组合导航AGV精确定位技术研究  

Research on precise positioning technology for AGV based on multi-object vision and laser integrated navigation

作　　者：何珍 楼佩煌[1,2] 钱晓明 武星[1,2] 朱立群 

机构地区：[1]南京航空航天大学机电学院,南京210016 [2]江苏省精密与微细制造技术重点实验室,南京210016

出　　处：《仪器仪表学报》2017年第11期2830-2838,共9页Chinese Journal of Scientific Instrument

基　　金：江苏省重点研发(BE2016004-3);中国博士后科学基金(2015M580421);汽车装配智能输送装备关键技术研发(BY2015003-11);江苏省普通高校研究生科研创新计划(SJZZ16_0058)项目资助

摘　　要：为进一步提高自动导引车(AGV)的定位精度,提出了一种多目视觉与激光组合导航的精确定位方法。该方法首先提出了一种基于双目视觉实时测量的AGV位姿控制技术,通过多目视觉系统来识别导引线侧的多个圆形标识点完成前瞻预判与精准定姿。采用基于代数距离方差校验的改进型最小二乘拟合椭圆算法来确定各标识中心坐标,结合激光扫描与视觉定位信息,采用无迹卡尔曼滤波算法进行多传感器信息融合,最终实现精确定位。实验结果表明:使用该方法后定位精度明显得到提高,控制曲线更为平滑,定位鲁棒性更好,姿态调整精度可达±0.5°,停车定位精度可达±1 mm。In order to further improve the positioning accuracy of AGV （Automated Guided Vehicle） and meet the requirements of high- precision positioning occasions, a precise positioning method based on binocular vision and laser integrated navigation is proposed in this paper. Firstly, the method proposes an AGV position and pose control technique based on binocular vision real-time measurement. The multi-object vision system is used to recognize a number of circular identification points on the guide wire side, and the forward looking prediction and accurate pose determination are completed. Then, the improved least squares fitting ellipse algorithm based on algebraic distance variance calibration is used to determine the coordinates of the identification centers. Combining laser scanning and visual positioning information, the Unscented Kalman Filter （UKF） algorithm is adopted to realize the multiple sensor data fusion; and finally, the accurate positioning is realized. Experiment results show that after using the proposed method, the positioning accuracy is improved obviously, the control curve becomes smoother, the positioning robustness becomes better; the attitude adjustment accuracy can reach to ＋ 0.5 degrees and the comprehensive parking positioning accuracy can reach to ＋ 1 mm.

关 键 词：自动导引小车 组合导航 无迹卡尔曼滤波 精确定位 

分 类 号：TP242.2[自动化与计算机技术—检测技术与自动化装置] TH741[自动化与计算机技术—控制科学与工程]