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논문 기본 정보

자료유형
학술저널
저자정보
Sukchang Yun (Konkuk University) Byoungjin Lee (Konkuk University) Yeon-Jo Kim (Konkuk University) Young Jae Lee (Konkuk University) Sangkyung Sung (Konkuk University)
저널정보
대한전기학회 Journal of Electrical Engineering & Technology Journal of Electrical Engineering & Technology Vol.11 No.6
발행연도
2016.11
수록면
1,846 - 1,856 (11page)

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초록· 키워드

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This study proposes a novel feature point initialization method in order to improve the accuracy of feature point positions by fusing a vision sensor and a lidar. The initialization is a process that determines three dimensional positions of feature points through two dimensional image data, which has a direct influence on performance of a 6-DoF bearing-only SLAM. Prior to the initialization, an extrinsic calibration method which estimates rotational and translational relationships between a vision sensor and lidar using multiple calibration tools was employed, then the feature point initialization method based on the estimated extrinsic calibration parameters was presented. In this process, in order to improve performance of the accuracy of the initialized feature points, an iterative automatic scaling parameter tuning technique was presented. The validity of the proposed feature point initialization method was verified in a 6-DoF bearing-only SLAM framework through an indoor and outdoor tests that compare estimation performance with the previous initialization method.

목차

Abstract
1. Introduction
2. Vision/Lidar Extrinsic Calibration
3. Vision/Lidar-Based Feature Point Initialization for 6-dof Bearing-only SLAM
4. Experiments
5. Conclusion
References

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UCI(KEPA) : I410-ECN-0101-2017-560-001327717