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- W2767073161 abstract "In this paper, we present an approach to simultaneous localization and mapping (SLAM) for RGB-D cameras like the Microsoft Kinectv2 that is capable of reconstructing volumetric 3D map without the aid of a graphics processing unit (GPU). For many robots, including flying robots and ground mobile robots, most of them build 3D maps, such as sparse or dense point cloud. However, these maps can not give any effective informations for navigation. Especially, these maps do not work when ground mobile robot needs performing a specific task with considering its height and width. We adopt the volumetric 3D map instead of point cloud to represent environment explored. Besides, we evaluate location accuracy, robustness and map compactness for the system on public dataset and private data. The experiments demonstrate that our system has higher location accuracy, better robustness and can save storage space." @default.
- W2767073161 created "2017-11-10" @default.
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- W2767073161 date "2017-07-01" @default.
- W2767073161 modified "2023-09-26" @default.
- W2767073161 title "A robust SLAM system with compact map" @default.
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- W2767073161 doi "https://doi.org/10.1109/icinfa.2017.8078922" @default.
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