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赵鹏程
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Personal Information
  • Supervisor of Master's Candidates
  • Name (Pinyin):Zhao Pengcheng
  • Date of Birth:1993-09-05
  • E-Mail:
  • Date of Employment:2019-12-07
  • Administrative Position:高级实验师
  • Education Level:With Certificate of Graduation for Doctorate Study
  • Business Address:武汉大学信息学部遥感信息工程学院（5号楼）315办公室
  • Gender:Male
  • Contact Information:+86 15972003670
  • Status:Employed
  • Alma Mater:武汉大学
  • Teacher College:School of Remote Sensing and Information Engineering
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Paper Publications
Current position: Home   >   Scientific Research   >   Paper Publications

An Improved A-LOAM 3D Mapping Method Based on Ultra-wide Field Angle of Multi-line Lidar

  • Date of Publication:2025-01-07
  • Hits:

  • DOI number: 

    10.1109/geoinformatics57846.2022.9963800

  • Affiliation of Author(s): 

    School of Remote Sensing and Information Engineering, Wuhan University, China

  • Journal: 

    International Conference on Geoinformatics

  • Key Words: 

    Indoor positioning systems,Mapping,3-D mapping,Dual-threshold ground filtering A-LOAM,Field angle,Ground filtering,Large field angle,Larger fields,Mapping method,Matchings,Point-clouds,Spatial 3d mapping,Optical radar,dual-threshold ground filtering A-LOAM,large field angle,lidar,spatial 3D mapping

  • Abstract: 

    Inter-frame matching of laser point clouds is the key to SLAM's autonomous positioning and 3D map construction. Aiming at the failure of inter frame matching of multi-line lidar SLAM during fast field of view conversion, this paper proposes a spatial 3D mapping method using 180 degree large-field-angle lidar to improve A-LOAM. Firstly, the nonground feature points are obtained by dual-threshold ground filtering, and a novel point cloud feature extraction method based on curvature is used to realize the feature point matching of large-field-angle point cloud; Secondly, using the matching methods of edge point to edge line and plane point to plane block, through the robust frame matching of large-field-angle point cloud data, the spatial 3D mapping is realized; Finally, three-dimensional mapping experiments are carried out on the large-field-angle point cloud data collected in different scenes. The results show that the spatial 3D mapping based on robust frame matching of large-field-angle lidar can reach the accuracy of nearly centimeter level in indoor scene and decimeter level in outdoor scene. It has application prospects in 3D mapping and other fields. © 2022 IEEE.

  • Co-author: 

    Zhao, Honggang, Xuan,Wu, Tianni, Qingwu,Yang,Wang,Hu, Pengcheng

  • Indexed by: 

    会议论文

  • Discipline: 

    Engineering

  • Document Type: 

    C

  • Volume: 

    2022-August

  • ISSN No.: 

    2161-024X

  • Translation or Not: 

    no

  • CN No.: 

    Scopus:2-s2.0-85143898742

  • Date of Publication: 

    2022-08-15

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