OverlapNet: Loop Closing for LiDAR-based SLAM
robotics science and systems, 2020.
II shows the comparison between our approach and the state of the art using the F1 score and the area under the curve on both KITTI and Ford campus dataset
Simultaneous localization and mapping (SLAM) is a fundamental capability required by most autonomous systems. In this paper, we address the problem of loop closing for SLAM based on 3D laser scans recorded by autonomous cars. Our approach utilizes a deep neural network exploiting different cues generated from LiDAR data for finding loop c...More
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