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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
作者部门水下机器人研究室
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
会议录名称Proceedings of the 30th Chinese Control and Decision Conference, CCDC 2018
出版者IEEE
出版地New York
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
文献类型会议论文
条目标识符http://ir.sia.cn/handle/173321/22392
专题水下机器人研究室
通讯作者Jiang M(蒋敏)
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
推荐引用方式
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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