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Article

Accumulative Errors Optimization for Visual Odometry of ORB-SLAM2 Based on RGB-D Cameras

1
School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430079, China
2
State Key Laboratory of Information Engineering in Surveying Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China
*
Author to whom correspondence should be addressed.
ISPRS Int. J. Geo-Inf. 2019, 8(12), 581; https://0-doi-org.brum.beds.ac.uk/10.3390/ijgi8120581
Received: 1 November 2019 / Revised: 2 December 2019 / Accepted: 9 December 2019 / Published: 11 December 2019
(This article belongs to the Special Issue 3D Indoor Mapping and Modelling)
Oriented feature from the accelerated segment test (oFAST) and rotated binary robust independent elementary features (rBRIEF) SLAM2 (ORB-SLAM2) represent a recognized complete visual simultaneous location and mapping (SLAM) framework with visual odometry as one of its core components. Given the accumulated error problem with RGB-Depth ORB-SLAM2 visual odometry, which causes a loss of camera tracking and trajectory drift, we created and implemented an improved visual odometry method to optimize the cumulative error. First, this paper proposes an adaptive threshold oFAST algorithm to extract feature points from images and rBRIEF is used to describe the feature points. Then, the fast library for approximate nearest neighbors strategy is used for image rough matching, the results of which are optimized by progressive sample consensus. The image matching precision is further improved by using an epipolar line constraint based on the essential matrix. Finally, the efficient Perspective-n-Point method is used to estimate the camera pose and a least-squares optimization problem is constructed to adjust the estimated value to obtain the final camera pose. The experimental results show that the proposed method has better robustness, higher image matching accuracy and more accurate determination of the camera motion trajectory. View Full-Text
Keywords: RGB-D cameras; image matching; visual odometry; accumulating drift; ORB-SLAM2 RGB-D cameras; image matching; visual odometry; accumulating drift; ORB-SLAM2
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MDPI and ACS Style

Qin, J.; Li, M.; Liao, X.; Zhong, J. Accumulative Errors Optimization for Visual Odometry of ORB-SLAM2 Based on RGB-D Cameras. ISPRS Int. J. Geo-Inf. 2019, 8, 581. https://0-doi-org.brum.beds.ac.uk/10.3390/ijgi8120581

AMA Style

Qin J, Li M, Liao X, Zhong J. Accumulative Errors Optimization for Visual Odometry of ORB-SLAM2 Based on RGB-D Cameras. ISPRS International Journal of Geo-Information. 2019; 8(12):581. https://0-doi-org.brum.beds.ac.uk/10.3390/ijgi8120581

Chicago/Turabian Style

Qin, Jiangying, Ming Li, Xuan Liao, and Jiageng Zhong. 2019. "Accumulative Errors Optimization for Visual Odometry of ORB-SLAM2 Based on RGB-D Cameras" ISPRS International Journal of Geo-Information 8, no. 12: 581. https://0-doi-org.brum.beds.ac.uk/10.3390/ijgi8120581

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