Acta Optica Sinica, Volume. 42, Issue 24, 2401007(2022)
Lidar Point Cloud Descriptor with Rotation and Translation Invariance in Dynamic Environment
[1] Li J, Shao J J, Wang R D et al. A SR-context loop-closure detection algorithm of lidar point clouds[J]. Acta Optica Sinica, 41, 2228002(2021).
[2] Li S P, Zhang T, Gao X et al. Semi-direct monocular visual and visual-inertial SLAM with loop closure detection[J]. Robotics and Autonomous Systems, 112, 201-210(2019).
[3] Meng Q Y, Guo H Y, Zhao X M et al. Loop-closure detection with a multiresolution point cloud histogram mode in lidar odometry and mapping for intelligent vehicles[J]. IEEE/ASME Transactions on Mechatronics, 26, 1307-1317(2021).
[4] Zhang H K, Chen N S, Dai Z X et al. A multi-level data fusion localization algorithm for SLAM[J]. Robot, 43, 641-652(2021).
[5] Zhou G Z, Yuan J, Gao H M et al. The 3D lidar point cloud descriptor based on structural unit soft-encoding in structured environment[J]. Robot, 42, 641-650(2020).
[6] Steder B, Ruhnke M, Grzonka S et al. Place recognition in 3D scans using a combination of bag of words and point feature based relative pose estimation[C], 1249-1255(2011).
[7] Salti S, Tombari F, di Stefano L. SHOT: unique signatures of histograms for surface and texture description[J]. Computer Vision and Image Understanding, 125, 251-264(2014).
[8] Wang Y, Sun Z Z, Xu C Z et al. LiDAR Iris for loop-closure detection[C], 5769-5775(2021).
[9] Shi X Y, Chai Z Q, Zhou Y et al. Global place recognition using an improved scan context for LIDAR-based localization system[C], 498-503(2021).
[10] Kim G, Kim A. Scan context: egocentric spatial descriptor for place recognition within 3D point cloud map[C], 4802-4809(2018).
[11] Wang H, Wang C, Xie L H. Intensity scan context: coding intensity and geometry relations for loop closure detection[C], 2095-2101(2020).
[12] Fan Y F, He Y C, Tan U X. Seed: a segmentation-based egocentric 3D point cloud descriptor for loop closure detection[C], 5158-5163(2021).
[13] Kim G, Choi S, Kim A. Scan context++: structural place recognition robust to rotation and lateral variations in urban environments[J]. IEEE Transactions on Robotics, 38, 1856-1874(2022).
[14] Li S X, Li G Y, Wang L et al. LiDAR/IMU tightly coupled real-time localization method[J]. Acta Automatica Sinica, 47, 1377-1389(2021).
[15] Park S, Wang S Y, Lim H et al. Curved-voxel clustering for accurate segmentation of 3D LiDAR point clouds with real-time performance[C], 6459-6464(2019).
[16] Zhou Z B, Yang M, Wang C X et al. ROI-cloud: a key region extraction method for LiDAR odometry and localization[C], 3312-3318(2020).
[17] Hu J, Liu H, Xu W C et al. Position detection algorithm of road obstacles based on 3D LiDAR[J]. Chinese Journal of Lasers, 48, 2410001(2021).
[18] Ren T Y, Wu R C. An acceleration algorithm of 3D point cloud registration based on iterative closet point[C], 271-276(2020).
[19] Geiger A, Lenz P, Stiller C et al. Vision meets robotics: the KITTI dataset[J]. The International Journal of Robotics Research, 32, 1231-1237(2013).
[20] Rusu R B, Cousins S. 3D is here: Point Cloud Library (PCL)[C], 12315963(2011).
[21] Culjak I, Abram D, Pribanic T et al. A brief introduction to OpenCV[C], 1725-1730(2012).
[22] Zhang C J, Zhang Y H. Research on SLAM loop closure detection method based on HHO algorithm[J]. Laser & Optoelectronics Progress, 58, 1215006(2021).
Get Citation
Copy Citation Text
Yaohui Chang, Niansheng Chen, Lei Rao, Songlin Cheng, Guangyu Fan, Xiaoyong Song, Dingyu Yang. Lidar Point Cloud Descriptor with Rotation and Translation Invariance in Dynamic Environment[J]. Acta Optica Sinica, 2022, 42(24): 2401007
Category: Atmospheric Optics and Oceanic Optics
Received: May. 11, 2022
Accepted: Jul. 11, 2022
Published Online: Dec. 14, 2022
The Author Email: Rao Lei (raol@sdju.edu.cn)