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Proceedings Paper

Simultaneous localization and mapping of mobile robot using a RGB-D camera
Author(s): Junqin Lin; Baoling Han; Zhuo Ge; Guanhao Liang; Jiahang Zhao
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Paper Abstract

Localization algorithm based on machine vision is a hot topic in the field of intelligent mobile robot.A fast method for mobile robot 3D SLAM (simultaneous localization and mapping) was presented to address the problem of 3D modeling in complex indoor environment. After filtering, the SIFT feature is extracted and matched between every two frames of the sequence. According to the camera calibration model and the image feature extraction and matching procedure, the association between two 3D point clouds was established. On the basis of the RANSAC (random sample consensus) algorithm, the correspondence based iterative closest point arithmetic model was solved to realize the robot’s precise localization effectively. With the key frame-to-frame selection mechanism, the 3D map method and the unique normal characteristic of a spatial point were used for maintaining and updating the global map. Experimental results demonstrate the feasibility and effectiveness of the proposed algorithm in the indoor environment.

Paper Details

Date Published: 31 October 2016
PDF: 10 pages
Proc. SPIE 10020, Optoelectronic Imaging and Multimedia Technology IV, 100200V (31 October 2016); doi: 10.1117/12.2245382
Show Author Affiliations
Junqin Lin, Beijing Institute of Technology (China)
Baoling Han, Beijing Institute of Technology (China)
Zhuo Ge, Beijing Institute of Technology (China)
Guanhao Liang, Beijing Institute of Technology (China)
Jiahang Zhao, Beijing Institute of Technology (China)


Published in SPIE Proceedings Vol. 10020:
Optoelectronic Imaging and Multimedia Technology IV
Qionghai Dai; Tsutomu Shimura, Editor(s)

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