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LiDAR iris for loop-closure detection
Wang,Ying1; Sun,Zezhou1; Xu,Cheng Zhong2; Sarma,Sanjay E.3; Yang,Jian1; Kong,Hui1
Source PublicationIEEE International Conference on Intelligent Robots and Systems
AbstractIn this paper, a global descriptor for a LiDAR point cloud, called LiDAR Iris, is proposed for fast and accurate loop-closure detection. A binary signature image can be obtained for each point cloud after several LoG-Gabor filtering and thresholding operations on the LiDAR-Iris image representation. Given two point clouds, their similarities can be calculated as the Hamming distance of two corresponding binary signature images extracted from the two point clouds, respectively. Our LiDAR-Iris method can achieve a pose-invariant loop-closure detection at a descriptor level with the Fourier transform of the LiDAR-Iris representation if assuming a 3D (x, y, yaw) pose space, although our method can generally be applied to a 6D pose space by re-aligning point clouds with an additional IMU sensor. Experimental results on five road-scene sequences demonstrate its excellent performance in loop-closure detection.
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Scopus ID2-s2.0-85094125691
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Document TypeConference paper
CollectionFaculty of Science and Technology
Affiliation1.Nanjing University of Science and Technology,School of Computer Science and Engineering,Nanjing,China
2.University of Macau,Department of Computer Science,Macau,Macao
3.MIT,Department of Mechanical Engineering,Cambridge,United States
Recommended Citation
GB/T 7714
Wang,Ying,Sun,Zezhou,Xu,Cheng Zhong,et al. LiDAR iris for loop-closure detection[C],2020:5769-5775.
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