Volume 37 Issue 4
Dec.  2023
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ZHANG Ruxiao, FANG Yu, YANG Hao, HANG Guanrong, TAO Hanzhong, NING Yeyan. Registration method for grid point cloud based on improved FPFH[J]. Journal of Shanghai University of Engineering Science, 2023, 37(4): 414-419. doi: 10.12299/jsues.21-0086
Citation: ZHANG Ruxiao, FANG Yu, YANG Hao, HANG Guanrong, TAO Hanzhong, NING Yeyan. Registration method for grid point cloud based on improved FPFH[J]. Journal of Shanghai University of Engineering Science, 2023, 37(4): 414-419. doi: 10.12299/jsues.21-0086

Registration method for grid point cloud based on improved FPFH

doi: 10.12299/jsues.21-0086
  • Received Date: 2022-05-19
  • Publish Date: 2023-12-30
  • An improved fast point feature histogram (FPFH) was proposed for the initial registration of grid point cloud. The neighborhood density was added as a point feature description on the basis of FPFH. When searching the corresponding points with k-dimensional tree (k-d tree), the Bhattacharyya distance was used as the index. This improved method was compared with FPFH in the simulation. Then, the test device was built to collect the grid’s surface point cloud data. The data were registered with improved FPFH method and iterative closest point (ICP). Test results show that the precision level of the matched point cloud is 1 μm and the error range of grid hole stays in ±(20~40) μm, which theoretically satisfy the precision requirement of the grid.
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