An improved ORB-SLAM algorithm for feature extraction

doi:10.13474/j.cnki.11-2246.2019.0070

测绘通报 ›› 2019, Vol. 0 ›› Issue (3): 16-20.doi: 10.13474/j.cnki.11-2246.2019.0070

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An improved ORB-SLAM algorithm for feature extraction

ZHANG Liangqiao^1,2, CHEN Guoliang^1,2, XU Xiaodong¹, LIAN Dajun³, WANG Rui^1,2

1. School of Environment Science and Spatial Informatics, China University of Mining and Technology, Xuzhou 221116, China;
2. NASG Key Laboratory of Land Environment and Disaster Monitoring, China University of Mining and Technology, Xuzhou 221116, China;
3. Suzhou University of Science and Technology, Suzhou 215009, China

Received:2018-05-24 Revised:2018-12-27 Online:2019-03-25 Published:2019-04-02

Abstract

Abstract: Aiming at the problem of poor real-time performance and trajectory drift in visual SLAM positioning in complex indoor environments,this paper proposes an ORB-SLAM algorithm based on image feature detection extraction method.The algorithm improves the efficiency and accuracy of image feature detection and matching in the front-end,introduces a closed-loop detection strategy to optimize camera pose trajectory,and improves positioning accuracy.The SIFT,SURF and ORB of different feature extraction algorithms are compared and analyzed in different sources.The robot motion trajectory is estimated by this algorithm.The relative pose error from the real trajectory is 0.144 8 m.Experiments show that the proposed method is feasible and robustness.

Key words: V-SLAM, image feature detection and matching, ORB-SLAM, loop detection, pose estimation

CLC Number:

P228

ZHANG Liangqiao, CHEN Guoliang, XU Xiaodong, LIAN Dajun, WANG Rui. An improved ORB-SLAM algorithm for feature extraction[J]. 测绘通报, 2019, 0(3): 16-20.

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An improved ORB-SLAM algorithm for feature extraction

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