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题名:
Scan registration for mechanical scanning imaging sonar using kD2D-NDT
作者: 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
作者部门: 水下机器人研究室
通讯作者: Jiang M(蒋敏)
会议名称: 30th Chinese Control and Decision Conference, CCDC 2018
会议日期: June 9-11, 2018
会议地点: Shenyang, China
会议录: Proceedings of the 30th Chinese Control and Decision Conference, CCDC 2018
会议录出版者: IEEE
会议录出版地: New York
出版日期: 2018
页码: 6425-6430
收录类别: EI
EI收录号: 20183205650200
产权排序: 1
ISBN号: 978-1-5386-1243-9
关键词: scan registration ; kD2D-NDT ; mechanical scanning imaging sonar
摘要: A 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.
语种: 英语
内容类型: 会议论文
URI标识: http://210.72.131.170/handle/173321/22454
Appears in Collections:水下机器人研究室_会议论文

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作者单位: 1.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:
Jiang M,Song SM,Li YP,et al. Scan registration for mechanical scanning imaging sonar using kD2D-NDT[C]. 30th Chinese Control and Decision Conference, CCDC 2018. Shenyang, China. June 9-11, 2018.Scan registration for mechanical scanning imaging sonar using kD2D-NDT.
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文件名: Scan registration for mechanical scanning imaging sonar using kD2D-NDT.pdf
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