High-precision registration algorithm of variable scale heterogeneous point clouds based on intrinsic shape signatures features

Chang Liu; Gaopeng Zhang; Hubing Du; Rong Lu; Jingwei Zhao

doi:10.1117/12.2654872

15 December 2022 High-precision registration algorithm of variable scale heterogeneous point clouds based on intrinsic shape signatures features

Chang Liu, Gaopeng Zhang, Hubing Du, Rong Lu, Jingwei Zhao

Author Affiliations +

Proceedings Volume 12478, Thirteenth International Conference on Information Optics and Photonics (CIOP 2022); 124783V (2022) https://doi.org/10.1117/12.2654872
Event: Thirteenth International Conference on Information Optics and Photonics (CIOP 2022), 2022, Xi'an, China

Abstract

Many space tasks, such as on-orbit servicing, space rendezvous and docking strongly rely on accurate relative position and posture collectively (referred to as pose) of spacecraft. The single measurement methods are limited to their respective advantages and disadvantages, which cannot meet the demand of non-cooperative target pose measurement in complex space situations. But due to different information sources, multi-source heterogeneous point cloud registration algorithms face problems such as noise impact, outliers, partial overlap of point clouds, difference in density of point clouds, inconsistent scales and so on. To solve this problem, based on the Scaling Iterative Closest Point (SICP) algorithm, this paper proposes a high-precision registration algorithm of variable scale heterogeneous point clouds based on intrinsic shape signatures (ISS) features. Firstly, the algorithm down samples the voxels of the point cloud to be aligned, sparseness the number of point clouds, and screens out some noise; Secondly, coarse alignment of the feature point clouds extracted by the ISS algorithm is performed by establishing a cost function containing the surface variance of the feature points and the module value of the Euclidean distance of the feature points from their centers of mass; Finally, the two-point clouds are finely aligned by the SICP algorithm. The experimental results show that the algorithm shows high robustness and well real-time performance, and can realize the accurate registration of multi-source heterogeneous point clouds with multi scales.

Citation Download Citation

Chang Liu, Gaopeng Zhang, Hubing Du, Rong Lu, and Jingwei Zhao "High-precision registration algorithm of variable scale heterogeneous point clouds based on intrinsic shape signatures features", Proc. SPIE 12478, Thirteenth International Conference on Information Optics and Photonics (CIOP 2022), 124783V (15 December 2022); https://doi.org/10.1117/12.2654872

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KEYWORDS

Clouds

Computer simulations

3D modeling

Data modeling

Detection and tracking algorithms

Nickel

Global Positioning System

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