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Scan registration for underwater mechanical scanning imaging sonar using symmetrical Kullback-Leibler divergence
Jiang M(蒋敏)1,2; Song SM(宋三明)1; Li YP(李一平)1; Tang FZ(唐凤珍)1; Liu J(刘健)1; Feng XS(封锡盛)1
Department水下机器人研究室
Source PublicationJOURNAL OF ELECTRONIC IMAGING
ISSN1017-9909
2019
Volume28Issue:1Pages:1-11
Indexed BySCI ; EI
EI Accession number20191106619744
WOS IDWOS:000460119700026
Contribution Rank1
Keywordunderwater robots mechanical scanning imaging sonar scan registration symmetrical Kullback-Leibler divergence
AbstractDue to its advantages in size and energy consumption, mechanical scanning imaging sonar (MSIS) has been widely used in portable and economic underwater robots to observe the turbid and noisy underwater environment. However, handicapped by the coarseness in spatial and temporal resolution, it is difficult to stitch the scan pieces together into a panoramic map for global understanding. A registration method named symmetrical Kullback-Leibler divergence (SKLD)-distribution-to-distribution (D2D), which models each scan as a Gaussian mixture model (GMM) and evaluates the similarity between two GMMs in a D2D way with the measure defined by SKLD, is proposed to register the scans collected by MSIS. SKLD not only weights the difference between distributions with the prior probability but also increases the numerical stability with the symmetrical constraint in distance measure. Moreover, an approximation strategy is designed to derive a tractable solution for the KLD between two GMMs. Experimental results on the scans that were collected from the realistic underwater environment demonstrate that SKLD-D2D dramatically reduces the computational cost without compromising the estimation precision. (C) 2019 SPIE and IS&T
Language英语
WOS SubjectEngineering, Electrical & Electronic ; Optics ; Imaging Science & Photographic Technology
WOS KeywordSLAM
WOS Research AreaEngineering ; Optics ; Imaging Science & Photographic Technology
Funding ProjectNational Key Research and Development Program of China[2016YFC0300801] ; Public Science and Technology Research Funds Projects of Ocean[201505017] ; National Natural Science Foundation of China ; National Natural Science Foundation of China[41506121] ; National Key Research and Development Program of China[2017YFC030 5901] ; National Key Research and Development Program of China[2016YFC0301601] ; Strategic Priority Program of the Chinese Academy of Sciences[XDA13030205] ; Strategic Priority Program of the Chinese Academy of Sciences[XDA11040103] ; State Key Laboratory of Robotics of China[2017-Z010] ; Natural Science Foundation of Jiangsu Province, China[BK20170558] ; project of R&D Center for Underwater Construction Robotics - Ministry of Ocean and Fisheries (MOF) ; Korea Institute of Marine Science & Technology Promotion (KIMST), Korea[PJT200539] ; National Key Research and Development Program of China ; Chinese Academy of Sciences ; State Key Laboratory of Robotics of China ; Natural Science Foundation of Jiangsu Province, China ; Ministry of Ocean and Fisheries (MOF) ; Korea Institute of Marine Science & Technology Promotion (KIMST), Korea ; Public science and technology research funds projects of ocean
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Document Type期刊论文
Identifierhttp://ir.sia.cn/handle/173321/24415
Collection水下机器人研究室
Corresponding AuthorSong SM(宋三明)
Affiliation1.Chinese Academy of Sciences, Shenyang Institute of Automation, State Key Laboratory of Robotics, Shenyang, China
2.University of Chinese Academy of Sciences, Beijing, China
Recommended Citation
GB/T 7714
Jiang M,Song SM,Li YP,et al. Scan registration for underwater mechanical scanning imaging sonar using symmetrical Kullback-Leibler divergence[J]. JOURNAL OF ELECTRONIC IMAGING,2019,28(1):1-11.
APA Jiang M,Song SM,Li YP,Tang FZ,Liu J,&Feng XS.(2019).Scan registration for underwater mechanical scanning imaging sonar using symmetrical Kullback-Leibler divergence.JOURNAL OF ELECTRONIC IMAGING,28(1),1-11.
MLA Jiang M,et al."Scan registration for underwater mechanical scanning imaging sonar using symmetrical Kullback-Leibler divergence".JOURNAL OF ELECTRONIC IMAGING 28.1(2019):1-11.
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