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Visual SLAM using Multiple RGB-D Cameras

IEEE-ROBIO 2015

Shaowu Yang     Xiaodong Yi     Zhiyuan Wang     Yanzhen Wang     Xuejun Yang

HPCL | School of Computer, National University of Defense Technology


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Abstract

In this paper, we present a solution to visual simultaneous localization and mapping (SLAM) using multiple RGB-D cameras. In the SLAM system, we integrate visual and depth measurements from those RGB-D cameras to achieve more robust pose tracking and more detailed environmental mapping in unknown environments. We present the mathematical analysis of the iterative optimizations for pose tracking and map refinement of a RGB-D SLAM system in multi-camera cases. The resulted SLAM system allows configurations of multiple RGB-D cameras with non-overlapping fields of view (FOVs). Furthermore, we provide a SLAM-based semi-automatic method for extrinsic calibration among such cameras. Finally, the experiments in complex indoor scenarios demonstrate the efficiency of the proposed visual SLAM algorithm.

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Acknowledgment

The authors would like to thank Prof. Andreas Zell and Sebastian A. Scherer, from the Department of Computer Science, University of Tuebingen, form helpful discussions and providing us the source code related to the work in [25].

This work is supported by Research on Foundations of Major Applications, Research Programs of NUDT, Project ZDYYJCYJ20140601, and NSFC Project 61303185, 61403409.

发布时间:2016-01-18 12:37
最后编辑:王彦臻
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创建时间:2016-01-18 12:24