基于SLAM导航的多目视觉AGV系统设计  

Design of Multi Vision AGV System Based on SLAM Navigation

作　　者：李俊 LI Jun(Modem Education Technology Center,Xinxiang Medical University,Xinxiang 453003,China)

机构地区：[1]新乡医学院现代教育技术中心,新乡453003

出　　处：《包装工程》2018年第19期181-189,共9页Packaging Engineering

摘　　要：目的为了进一步提高SLAM定位精度和小障碍物识别能力。方法采用SLAM与多目视觉结合的方法,首先构建AGV运动学模型,然后构建双目立体视觉模型,基于SURF+RANSAC改进的分区域加权算法,尽可能剔除冗余误匹配对,显著提高匹配精度。其次,在传统SLAM导航基础上融入单目视觉,实现关键工位点精确定位停靠,并给出二维码遮挡缺损情况下的解决方法,采用双目视觉实现距离实时测量。结果双目距离检测精度可达±1.88 mm,轨迹精度可以控制在±2 mm。结论融合SLAM和多目视觉可以有效提高导航定位精度和小障碍物识别能力,提高了SLAM的应用领域,具有一定的推广前景。The work aims to further improve SLAM positioning accuracy and small obstacle recognition ability. The method combined with SLAM and multi-vision was used to set up the AGV kinematics model and then construct the binocular stereo vision model. The improved subregional weighting algorithm based on SURF＋RANSAC could eliminate the redundant matching pairs to the greatest extent and improve the matching accuracy significantly. Secondly, on the basis of traditional SLAM navigation, monocular vision was integrated to achieve precise positioning and berthing of key workstations and propose a solution for the occlusion defect of two-dimensional code. Real-time distance measurement was realized by binocular vision. The accuracy of binocular distance detection reached ±1.88 mm and the track cy could be controlled at ±2 mm. Fusion of SLAM and multi-vision can effectively improve the accuracy of navigation and positioning and the small obstacle recognition and expand the application of SLAM, so it has a certain prospect of promotion.

关 键 词：SLAM 立体视觉 单目视觉 SURF RANSAC 分区加权 

分 类 号：TB486[一般工业技术—包装工程] TP242[自动化与计算机技术—检测技术与自动化装置]