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有色金属(矿山部分):2019,71(5):6-9
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三维激光扫描点云数据盲区边界识别与应用
(1.(1.北京矿冶科技集团有限公司,北京 100160;2.北京科技大学 机械工程学院,北京 100083;3.金属矿山智能开采技术北京市重点实验室,北京 102628))
Blind area recognition and application for point cloud data of 3D laser scanner
(1.(1. BGRIMM Technology Group, Beijing 100160, China;2. College of Mechanics Engineering, Beijing University of Science and Technology, Beijing 100083, China;3. Beijing Key Laboratory of Nonferrous Intelligent Mining Technology, Beijing 102628, China))
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中文摘要: 三维激光扫描仪是一款获取空间点云数据的测量设备,能够有效地获取被测物体三维空间形态,但是,由于被测对象空间形态复杂、人员难于进入等原因,导致扫描点云数据存在盲区且识别困难。针对该问题,采用了一种三维激光扫描点云数据盲区识别方法,可获取点云数据盲区边界,该方法主要通过对点云数据进行KD-Tree改造,然后估计点云数据法式,最后提取点云数据边界。为验证本文提出的盲区识别算法,选取矿山采空区点云数据进行实际验证,可准确识别点云数据边界信息,为后续数据进一步利用提供了基础。
Abstract:3D laser scanner is a measurement equipment which can show 3D sharp and obtain point cloud of object. However, point cloud will form blind area and be difficult to recognize because survived object’s sharp is complex and people can’t enter to these dangerous area. To solve this problem, a blind area recognition method for point cloud data of 3D laser scanner was used in the present work, which method can accurately recognize blind area of point cloud which mainly create KD-Tree of point cloud, calculate normal vector of point cloud and extract boundary of point cloud. Moreover, point cloud data of cavity was chosen to verify blind area recognition method, results indicated this method can recognize blind area of point cloud data accurately.
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基金项目:“十三五”国家重点研发计划项目(2017YFC0804600,2017YFC0804606);国家高技术研究发展计划项目(2011AA060405)。
引用文本:
陈 凯1,2,3,张 达1,3,张元生1,3.三维激光扫描点云数据盲区边界识别与应用[J].有色金属(矿山部分),2019,71(5):6-9.
CHEN Kai1,2,3,ZHANG Da1,ZHANG Yuansheng1,3.Blind area recognition and application for point cloud data of 3D laser scanner[J].NONFERROUS METALS(Mining Section),2019,71(5):6-9.

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