MNE-SLAM: Multi-Agent Neural SLAM for Mobile Robots
Tianchen Deng, Guole Shen, Chen Xun, Shenghai Yuan, Tongxin Jin, Hongming Shen, Yanbo Wang, Jingchuan Wang, Hesheng Wang, Danwei Wang, Weidong Chen
Abstract
Figure 1 . We present MNE-SLAM, the first distributed multi-agent collaborative SLAM system with distributed mapping and camera tracking, joint implicit neural scene representation, intra-to-inter loop closure, and multiple submap fusion. Depicted at the bottom, we demonstrate the real-world, large-scale long-corridor scenes (≈1000 m 2 ) with high-accuracy 3D groundtruth mesh. This scene is collected through various industrial laser scans. We display the rendered depth and color image of different type of agents around the corridor. The trajectory of each agent is marked in a unique color for clarity.
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Cited by top-tier papers8
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- DROID-SLAM: Deep Visual SLAM for Monocular, Stereo, and RGB-D CamerasZachary Teed, Jia DengNeurIPS 2021 · 1,248 citations
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- ScanNet++: A High-Fidelity Dataset of 3D Indoor ScenesChandan Yeshwanth, Yueh-Cheng Liu, Matthias Nießner, Angela DaiICCV 2023 · 659 citations
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