Stereo RGB-D indoor mapping with precise stream fusing strategy

Tang, Shengjun; Wang, Weixi; Li, Xiaoming; Yuan, Zhilu

In order to achieve more robust pose tracking and mapping of visual SLAM, the robotics researcher has recently shown a growing interest in utilising multiple camera, which is able to provide more sufficient observations to fulfil the frame registration and map updating tasks. This implies that better pose tracking robustness can be achieved by extending monocular visual SLAM to utilise measurements from multiple cameras.[1] proposed a visual SLAM method using multiple RGB-D cameras, which integrate the observations from multi-camera for camera tracking. However, they ignored the time-drift between the frames obtained by different cameras, which may result at inaccurate positions of observation used for map updating. Besides, loop closure detection was not been implemented. [2] constructed a multiple RGB-D system with three Kinects V2 camera. This work mainly concentrated on the intrinsic and extrinsic calibration and verify the effectiveness of mapping using multiply RGB-D cameras.

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Tang, Shengjun / Wang, Weixi / Li, Xiaoming / et al: Stereo RGB-D indoor mapping with precise stream fusing strategy. 2019. Copernicus Publications.

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