Sensors 2016, 16(8), 1285; doi:10.3390/s16081285
RGB-D SLAM Based on Extended Bundle Adjustment with 2D and 3D Information
1
State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, No. 20A, Datun Road, Chaoyang District, Beijing 100101, China
2
University of Chinese Academy of Sciences, Beijing 100049, China
*
Author to whom correspondence should be addressed.
Academic Editors: Gabriel Oliver-Codina, Nuno Gracias and Antonio M. López
Received: 27 May 2016 / Revised: 4 August 2016 / Accepted: 9 August 2016 / Published: 13 August 2016
(This article belongs to the Special Issue Vision-Based Sensors in Field Robotics)
Abstract
In the study of SLAM problem using an RGB-D camera, depth information and visual information as two types of primary measurement data are rarely tightly coupled during refinement of camera pose estimation. In this paper, a new method of RGB-D camera SLAM is proposed based on extended bundle adjustment with integrated 2D and 3D information on the basis of a new projection model. First, the geometric relationship between the image plane coordinates and the depth values is constructed through RGB-D camera calibration. Then, 2D and 3D feature points are automatically extracted and matched between consecutive frames to build a continuous image network. Finally, extended bundle adjustment based on the new projection model, which takes both image and depth measurements into consideration, is applied to the image network for high-precision pose estimation. Field experiments show that the proposed method has a notably better performance than the traditional method, and the experimental results demonstrate the effectiveness of the proposed method in improving localization accuracy. View Full-TextKeywords:
RGB-D camera; SLAM; projection model; bundle adjustment; Kinect
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MDPI and ACS Style
Di, K.; Zhao, Q.; Wan, W.; Wang, Y.; Gao, Y. RGB-D SLAM Based on Extended Bundle Adjustment with 2D and 3D Information. Sensors 2016, 16, 1285.
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