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Scan registration for mechanical scanning imaging sonar using kD2D-NDT
Jiang M(蒋敏)1,2; Song SM(宋三明)1; Li YP(李一平)1; Liu J(刘健)1; Feng XS(封锡盛)1
Department水下机器人研究室
Conference Name30th Chinese Control and Decision Conference, CCDC 2018
Conference DateJune 9-11, 2018
Conference PlaceShenyang, China
Source PublicationProceedings of the 30th Chinese Control and Decision Conference, CCDC 2018
PublisherIEEE
Publication PlaceNew York
2018
Pages6425-6430
Indexed ByEI
EI Accession number20183205650200
Contribution Rank1
ISBN978-1-5386-1243-9
Keywordscan registration kD2D-NDT mechanical scanning imaging sonar
AbstractA method derived from the D2D-NDT, named kD2D-NDT, is proposed to register the scans that are collected by the Mechanical Scanning Imaging Sonar (MSIS). The D2D-NDT method replaces the point-to-distribution (P2D) scoring in the normal distribution transformation (NDT) with distribution-to-distribution (D2D) matching, greatly reducing the computation cost. In this paper, several heuristic strategies are adopted in kD2D-NDT to accelerate and stabilize the matching process. Firstly, the point cloud of the floating scan and the reference scan are grouped into compact clusters by the K-means clustering method to accommodate the Gaussian mixture model assumption which underlies the D2D distance measure and no iterative optimization at different grid size is needed. Secondly, for each Gaussian component in the floating scan, only k =3D 3 nearest Gaussian components in the reference scan are chosen to measure the similarity. Lastly, to avoid the singularity in calculating the matrix inverse, the Euclidean distance between the centroid pair, instead of the Mahalanobis distance, is adopted to find the most similar Gaussian components. Its applications to the scans that are collected from the realistic underwater environment show that the proposed strategies make kD2D-NDT practical for the MSIS scans.
Language英语
Document Type会议论文
Identifierhttp://ir.sia.cn/handle/173321/22392
Collection水下机器人研究室
Corresponding AuthorJiang M(蒋敏)
Affiliation1.State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China
2.University of Chinese Academy of Sciences, Beijing 100049, China
Recommended Citation
GB/T 7714
Jiang M,Song SM,Li YP,et al. Scan registration for mechanical scanning imaging sonar using kD2D-NDT[C]. New York:IEEE,2018:6425-6430.
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