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RGB-D SLAM增强现实原木检尺系统构建与测试

Construction and Testing of RGB-D SLAM Augmented Reality Log Measurement System
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摘要 将内嵌有ToF相机、面阵相机及IMU的智能手机作为硬件系统,RGB-D SLAM技术实时获取的深度图、位姿等为数据源,构建了RGB-D SLAM增强现实楞堆原木检尺系统。首先设计了基于ToF影像实时估计RGB影像像素深度的方法,实现对待测原木端面几何坐标的初步估计;其次,设计了散形分区去噪算法实现原木端面点云的精确过滤,设计了原木端面曲率估计算法实现对过滤点云可靠性判别;然后,基于PCA等算法实现原木长、短直径方向向量估计,并基于该向量对原木长、短直径进行了估计;最后,以所构建算法为基础在智能手机平台上搭建了增强现实楞堆检尺系统,实现智能手机对原木进行实时检尺、增强现实场景对测量结果实时监督。新型检尺系统通过对6个楞堆334根原木进行了检尺实验,以评估该设备的测量精度。结果显示:原木平均直径估计值的偏差及均方根误差分别为-0.13 cm(-0.35%)及1.05 cm(3.34%);原木径阶化直径估计值的偏差及均方根误差分别为-0.10 cm(-0.22%)及1.33 cm(4.43%);原木材积估计值的偏差及均方根误差分别为-0.007 m^(3)(-0.27%)及0.093 9 m^(3)(7.23%);楞堆材积相对误差绝对值均不大于2.23%,所有楞堆总材积相对误差为-0.68%。无论从单根原木还是楞堆角度来看,材积等测量结果均无偏且高精度,说明原木检尺系统是一种可高精度、高鲁棒性实时完成楞堆原木检尺的潜在方案。 The RGB-D SLAM augmented reality log measurement system was constructed,which used a smart phone embedded with a ToF camera,RGB camera and IMU as the hardware system,and used the depth map and pose acquired by RCB-D SLAM technology as the data source.Specifically,the method for online estimating the pixel depth of RGB images was designed based on ToF images in order to preliminarily estimate the position of log end faces;secondly,a denoising algorithm based on discrete partitioning and a log end face curvature estimation algorithm were designed for precisely filtering the log end point cloud and evaluating the reliability of the filtering results;then,the PCA algorithm was used to estimate the length and diameter direction vector of the log,which was used to estimate the value of the length and diameter of the log;and finally,the algorithm was used to build a log measurement system on the mobile phone platform,so as to realize the online measurement of the log diameter by using the smart phone,and the online supervision of the measurement results by using the augmented reality scene.The system was tested by measuring 334 logs in six regions to evaluate the measurement accuracy.The results showed that the bias and root mean square error(RMSE)of the log diameter estimates were-0.13 cm(-0.35%)and 1.05 cm(3.34%)respectively;the bias and RMSE of the log stepping diameter estimates were-0.10 cm(-0.22%)and 1.33 cm(4.43%)respectively;the bias and RMSE of the log volume estimates were-0.007 m^(3)(-0.27%)and 0.0939 m^(3)(7.23%)respectively;the absolute value of the relative error of the volume of log pile was no more than 2.23%;and the error of the total volume of all log piles was-0.68%.Obviously,no matter from the point of view of a single log or a pile,the measurement results were unbiased and high-precision,which meant that the new log measuring system was a potential high-precision,high-robust real-time log measuring potential solutions.
作者 范永祥 冯仲科 苏珏颖 韦泽波 申朝永 闫飞 FAN Yongxiang;FENG Zhongke;SU Jueying;WEI Zebo;SHEN Chaoyong;YAN Fei(Jihua Laboratory,Foshan 528000,China;Precision Forestry Key Laboratory of Beijing,Bejing Forestry University,Beijing 100083,China;Natural Resources Technology Information Center of Guizhou Province,Guiyang 550004,China)
出处 《农业机械学报》 EI CAS CSCD 北大核心 2023年第12期280-287,共8页 Transactions of the Chinese Society for Agricultural Machinery
基金 广东省基础与应用基础研究基金项目(2020A1515110253)。
关键词 原木检尺 ToF相机 实时SLAM 增强现实 log measurement ToF camera online SLAM augmented reality
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