Journal of System Simulation
Abstract
Abstract: Aiming at the pose measurement caused by non-cooperative targets in visual measurement that cannot provide cooperation information,the ICP(Iterative Closest Point) algorithm is used to register the point cloud down-sampling data acquired at different times to complete the relative pose measurement of the target.The point cloud data of the target at the current moment is obtained using the structure from motion algorithm and the feature point matching algorithms are compared based on threshold matching and optical flow matching method.The extracted feature points are reconstructed by triangulation.The relative pose changes of the object at different times are calculated by using the downsampling point cloud data.Experiments show that when the object rotates,the maximum error of the rotation angle using the ICP algorithm does not exceed 0.11º.
Recommended Citation
Liang, Wei; Xue, Muyao; Ju, Huo; and Zhang, Jinjie
(2020)
"Non-cooperative Target Feature Point Cloud Registration Optimization Based on ICP Algorithm,"
Journal of System Simulation: Vol. 32:
Iss.
12, Article 10.
DOI: 10.16182/j.issn1004731x.joss.20-FZ0478
Available at:
https://dc-china-simulation.researchcommons.org/journal/vol32/iss12/10
First Page
2383
Revised Date
2020-07-12
DOI Link
https://doi.org/10.16182/j.issn1004731x.joss.20-FZ0478
Last Page
2387
CLC
TP391.9
Recommended Citation
Wei Liang, Xue Muyao, Huo Ju, Zhang Jinjie. Non-cooperative Target Feature Point Cloud Registration Optimization Based on ICP Algorithm[J]. Journal of System Simulation, 2020, 32(12): 2383-2387.
DOI
10.16182/j.issn1004731x.joss.20-FZ0478
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