Abstract
This paper presents a novel RGB-D SLAM algorithm for reconstructing a 3D surface in indoor environment. The method is a submap joining based RGB-D SLAM algorithm using planes as features and hence is called SJBPF-SLAM. Two adjacent keyframes, with the corresponding small patches and planes observed from the keyframes, are used to build a submap. Then the current submap is fused to the global map sequentially, meanwhile the global structure is recovered gradually through plane feature associations. The use of submap significantly reduces the computational cost during the optimization process, without losing any information about planes and structures. The proposed method is validated using publicly available RGB-D benchmarks and obtains good quality trajectory and 3D models, which are difficult for existing RGB-D SLAM algorithms.
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Wang, J., Song, J., Zhao, L., Huang, S. (2018). A Submap Joining Based RGB-D SLAM Algorithm Using Planes as Features. In: Hutter, M., Siegwart, R. (eds) Field and Service Robotics. Springer Proceedings in Advanced Robotics, vol 5. Springer, Cham. https://doi.org/10.1007/978-3-319-67361-5_24
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DOI: https://doi.org/10.1007/978-3-319-67361-5_24
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