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Sensors 2015, 15(8), 18742-18766;

RGB-D SLAM Combining Visual Odometry and Extended Information Filter

School of Information Engineering, East China Jiaotong University, Nanchang 330013, China
Department of Mechanical, Aerospace and Biomedical Engineering, University of Tennessee, Knoxville, TN 37996, USA
School of Computer Science, Colorado Technical University, Colorado Springs, CO 80907, USA
Author to whom correspondence should be addressed.
Academic Editor: Vittorio M.N. Passaro
Received: 21 May 2015 / Revised: 20 July 2015 / Accepted: 27 July 2015 / Published: 30 July 2015
(This article belongs to the Special Issue Sensors for Robots)
Full-Text   |   PDF [1150 KB, uploaded 30 July 2015]   |  


In this paper, we present a novel RGB-D SLAM system based on visual odometry and an extended information filter, which does not require any other sensors or odometry. In contrast to the graph optimization approaches, this is more suitable for online applications. A visual dead reckoning algorithm based on visual residuals is devised, which is used to estimate motion control input. In addition, we use a novel descriptor called binary robust appearance and normals descriptor (BRAND) to extract features from the RGB-D frame and use them as landmarks. Furthermore, considering both the 3D positions and the BRAND descriptors of the landmarks, our observation model avoids explicit data association between the observations and the map by marginalizing the observation likelihood over all possible associations. Experimental validation is provided, which compares the proposed RGB-D SLAM algorithm with just RGB-D visual odometry and a graph-based RGB-D SLAM algorithm using the publicly-available RGB-D dataset. The results of the experiments demonstrate that our system is quicker than the graph-based RGB-D SLAM algorithm. View Full-Text
Keywords: SLAM; visual odometry; extended information filter; binary descriptor SLAM; visual odometry; extended information filter; binary descriptor

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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Zhang, H.; Liu, Y.; Tan, J.; Xiong, N. RGB-D SLAM Combining Visual Odometry and Extended Information Filter. Sensors 2015, 15, 18742-18766.

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