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- W2720956875 abstract "Simultaneous Localization and Mapping (SLAM) of a mobile robot based on visual method has been extensively studied in the field of mobile robot navigation research, and most of the research in this field mainly focuses on how to obtain high quality robust features and can achieve better matching and to achieve large-scale, real-time SLAM. Firstly, the basic principles of simultaneous vision and map construction are briefly introduced. In order to solve the problem that the distortion can fall into the local optimal solution, an improved algorithm of monocular camera internal parameter calibration algorithm based on improved camera calibration parameters is proposed. In the feature point extraction and matching, based on the scale invariance of the SURF algorithm, the improvement of the ORB algorithm is analyzed. It not only preserves the fastness of the ORB algorithm, but also avoids the scale invariance defect, so that the accuracy and real-time of the algorithm have been further improved. Finally, summarize the results of this paper and the future work of the future." @default.
- W2720956875 created "2017-06-30" @default.
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- W2720956875 date "2017-04-07" @default.
- W2720956875 modified "2023-09-24" @default.
- W2720956875 title "The Application of Monocular Vision Camera Calibration and Feature Matching in SLAM" @default.
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- W2720956875 doi "https://doi.org/10.1145/3080845.3080876" @default.
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