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Dense RGB-D SLAM with Multiple Cameras
Meng, Xinrui1,2; Gao, Wei1,2; Hu, Zhanyi1,2
Source PublicationSENSORS
2018-07-01
Volume18Issue:7
SubtypeArticle
AbstractA multi-camera dense RGB-D SLAM (simultaneous localization and mapping) system has the potential both to speed up scene reconstruction and to improve localization accuracy, thanks to multiple mounted sensors and an enlarged effective field of view. To effectively tap the potential of the system, two issues must be understood: first, how to calibrate the system where sensors usually shares small or no common field of view to maximally increase the effective field of view; second, how to fuse the location information from different sensors. In this work, a three-Kinect system is reported. For system calibration, two kinds of calibration methods are proposed, one is suitable for system with inertial measurement unit (IMU) using an improved hand eye calibration method, the other for pure visual SLAM without any other auxiliary sensors. In the RGB-D SLAM stage, we extend and improve a state-of-art single RGB-D SLAM method to multi-camera system. We track the multiple cameras' poses independently and select the one with the pose minimal-error as the reference pose at each moment to correct other cameras' poses. To optimize the initial estimated pose, we improve the deformation graph by adding an attribute of device number to distinguish surfels built by different cameras and do deformations according to the device number. We verify the accuracy of our extrinsic calibration methods in the experiment section and show the satisfactory reconstructed models by our multi-camera dense RGB-D SLAM. The RMSE (root-mean-square error) of the lengths measured in our reconstructed mode is 1.55 cm (similar to the state-of-art single camera RGB-D SLAM systems).
KeywordMulti-camera Slam Calibration Rgb-d
WOS HeadingsScience & Technology ; Physical Sciences ; Technology
DOI10.3390/s18072118
WOS KeywordCALIBRATION
Indexed BySCI
Language英语
Funding OrganizationNational Key R&D Program of China(2016YFB0502002) ; National Natural Science Foundation of China (NSFC)(61333015 ; 61472419 ; 61421004)
WOS Research AreaChemistry ; Electrochemistry ; Instruments & Instrumentation
WOS SubjectChemistry, Analytical ; Electrochemistry ; Instruments & Instrumentation
WOS IDWOS:000441334300140
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Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/21824
Collection模式识别国家重点实验室_机器人视觉
Affiliation1.Chinese Acad Sci, Inst Automat, NLPR, Beijing 100190, Peoples R China
2.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing 100049, Peoples R China
Recommended Citation
GB/T 7714
Meng, Xinrui,Gao, Wei,Hu, Zhanyi. Dense RGB-D SLAM with Multiple Cameras[J]. SENSORS,2018,18(7).
APA Meng, Xinrui,Gao, Wei,&Hu, Zhanyi.(2018).Dense RGB-D SLAM with Multiple Cameras.SENSORS,18(7).
MLA Meng, Xinrui,et al."Dense RGB-D SLAM with Multiple Cameras".SENSORS 18.7(2018).
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