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机器人二维码目标点识别与SLAM地图标记研究
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促进高校内涵发展-学科建设专项资助项目(5112011015)


Research on Target Recognition of Robot Quick Response Code and SLAM Map Marking
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    摘要:

    用机器人将货物送至指定的二维码目标点时,使用的即时定位与地图构建(SLAM)算法为Cartographer。为识别二维码目标点并标记在SLAM创建的地图上,提出一种基于ZBar算法和融合Cartographer-SLAM与Hector-SLAM算法的方法对二维码目标点进行识别并标记。利用ZBar算法对摄像头捕捉到的二维码进行识别;采用Cartographer算法编写相应的服务即节点通信并生成Geotiff格式地图;保存地图时调用Hector-SLAM算法将目标点绘制在生成的Geotiff地图上。结果表明:与基于ZBar算法和Hector-SLAM算法进行二维码识别、建图与标记的方法相比,所提方法能在距目标点更远的地方识别到二维码且目标点位置标记更精确,误差更小,平均精度可提高67.6%。

    Abstract:

    When the robot is to deliver goods to the designated quick response(QR) code target points,the simultaneous localization and mapping(SLAM) algorithm is Cartographer.In order to identify and mark the QR code target points on the map created by using SLAM,a method based on ZBar algorithm and combining Cartographer-SLAM and Hector-SLAM algorithm was proposed to identify and mark the target points of the QR code.The ZBar algorithm was used to identify the QR code captured by the camera;the Cartographer algorithm was used to write the corresponding service namely node communication and generate the Geotiff format map;when saving the map,the Hector-SLAM algorithm was called to draw the target point on the generated Geotiff map.The results show that compared with the method of QR code recognition,mapping and marking based on ZBar algorithm and Hector-SLAM algorithm,by using the proposed method,the QR code can be recognized and the target point can be mark at a place farther away from the target point with less error,and the average accuracy can be improved by 67.6%.

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支奕琛,谷玉海,龚志力,宋亮.机器人二维码目标点识别与SLAM地图标记研究[J].机床与液压,2022,50(15):20-24.
ZHI Yichen, GU Yuhai, GONG Zhili, SONG Liang. Research on Target Recognition of Robot Quick Response Code and SLAM Map Marking[J]. Machine Tool & Hydraulics,2022,50(15):20-24

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  • 在线发布日期: 2023-01-17
  • 出版日期: 2022-08-15