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This paper presents FAST-LIO2: a fast, robust, and versatile LiDAR-inertial odometry framework.
J. L. Bentley, “Multidimensional binary search trees used for associative searching,” Communications of the ACM , vol. 18, no. 9, pp. 509–517, 1975
1975
Earlier work this paper cites.
J. H. Friedman, J. L. Bentley, and R. A. Finkel, “an algorithm for finding best matches in logarithmic expected time,” ACM Transactions on Mathematical Software (TOMS) , vol. 3, no. 3, pp. 209–226, 1977
1977
Earlier work this paper cites.
J. L. Bentley and J. B. Saxe, “Decomposable searching problems i: Static-to-dynamic transformation,” J. algorithms , vol. 1, no. 4, pp. 301–358, 1980
1980
Earlier work this paper cites.
D. Meagher, “Geometric modeling using octree encoding,” Computer graphics and image processing , vol. 19, no. 2, pp. 129–147, 1982
1982
Earlier work this paper cites.
A. Guttman, “R-trees: A dynamic index structure for spatial searching,” in Proceedings of the 1984 ACM SIGMOD international conference on Management of data , 1984, pp. 47–57
1984
Earlier work this paper cites.
M. H. Overmars, The design of dynamic data structures . Springer Science & Business Media, 1987, vol. 156
1987
Earlier work this paper cites.
N. Beckmann, H.-P. Kriegel, R. Schneider, and B. Seeger, “The r*-tree: An efficient and robust access method for points and rectangles,” in Proceedings of the 1990 ACM SIGMOD international conference on Management of data , 1990, pp. 322–331
1990
Earlier work this paper cites.
I. Galperin and R. L. Rivest, “Scapegoat trees.” in SODA , vol. 93, 1993, pp. 165–174
1993
Earlier work this paper cites.
S. Arya and D. Mount, “Ann: library for approximate nearest neighbor searching,” in Proceedings of IEEE CGC Workshop on Computational Geometry, Providence, RI , 1998
1998
Earlier work this paper cites.
P. Chanzy, L. Devroye, and C. Zamora-Cura, “Analysis of range search for random kd trees,” Acta informatica , vol. 37, no. 4-5, pp. 355–383, 2001
2001
Earlier work this paper cites.
G. C. Sharp, S. W. Lee, and D. K. Wehe, “Icp registration using invariant features,” IEEE Transactions on Pattern Analysis and Machine Intelligence , vol. 24, no. 1, pp. 90–102, 2002
2002
Earlier work this paper cites.
P. Biber and W. Straßer, “The normal distributions transform: A new approach to laser scan matching,” in Proceedings 2003 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2003)(Cat. No. 03CH37453) , vol. 3. IEEE, 2003, pp. 2743–2748
2003
Earlier work this paper cites.
O. Procopiuc, P. K. Agarwal, L. Arge, and J. S. Vitter, “Bkd-tree: A dynamic scalable kd-tree,” in International Symposium on Spatial and Temporal Databases . Springer, 2003, pp. 46–65
2003
Earlier work this paper cites.
K.-L. Low, “Linear least-squares optimization for point-to-plane icp surface registration,” Chapel Hill, University of North Carolina , vol. 4, no. 10, pp. 1–3, 2004
2004
Earlier work this paper cites.
S. Thrun, M. Montemerlo, H. Dahlkamp, D. Stavens, A. Aron, J. Diebel, P. Fong, J. Gale, M. Halpenny, G. Hoffmann, et al. , “Stanley: The robot that won the darpa grand challenge,” Journal of field Robotics , vol. 23, no. 9, pp. 661–692, 2006
2006
Earlier work this paper cites.
W. Hunt, W. R. Mark, and G. Stoll, “Fast kd-tree construction with an adaptive error-bounded heuristic,” in 2006 IEEE Symposium on Interactive Ray Tracing . IEEE, 2006, pp. 81–88
2006
Earlier work this paper cites.
S. Popov, J. Gunther, H.-P. Seidel, and P. Slusallek, “Experiences with streaming construction of sah kd-trees,” in 2006 IEEE Symposium on Interactive Ray Tracing . IEEE, 2006, pp. 89–94
2006
Earlier work this paper cites.
M. Shevtsov, A. Soupikov, and A. Kapustin, “Highly parallel fast kd-tree construction for interactive ray tracing of dynamic scenes,” Computer Graphics Forum , vol. 26, no. 3, pp. 395–404, 2007
2007
Earlier work this paper cites.
C. Urmson, J. Anhalt, D. Bagnell, C. Baker, R. Bittner, M. Clark, J. Dolan, D. Duggins, T. Galatali, C. Geyer, et al. , “Autonomous driving in urban environments: Boss and the urban challenge,” Journal of Field Robotics , vol. 25, no. 8, pp. 425–466, 2008
2008
Earlier work this paper cites.
K. Zhou, Q. Hou, R. Wang, and B. Guo, “Real-time kd-tree construction on graphics hardware,” ACM Transactions on Graphics , vol. 27, no. 5, pp. 1–11, 2008
2008
Earlier work this paper cites.
A. Segal, D. Haehnel, and S. Thrun, “Generalized-icp.” in Robotics: science and systems , vol. 2, no. 4. Seattle, WA, 2009, p. 435
2009
Earlier work this paper cites.
M. Magnusson, “The three-dimensional normal-distributions transform: an efficient representation for registration, surface analysis, and loop detection,” Ph.D. dissertation, Örebro universitet, 2009
2009
Cited alongside, same era.
M. Magnusson, A. Nuchter, C. Lorken, A. J. Lilienthal, and J. Hertzberg, “Evaluation of 3d registration reliability and speed-a comparison of icp and ndt,” in 2009 IEEE International Conference on Robotics and Automation . IEEE, 2009, pp. 3907–3912
2009
Cited alongside, same era.
M. Muja and D. G. Lowe, “Fast approximate nearest neighbors with automatic algorithm configuration.” VISAPP (1) , vol. 2, no. 331-340, p. 2, 2009
2009
Cited alongside, same era.
J. Levinson, J. Askeland, J. Becker, J. Dolson, D. Held, S. Kammel, J. Z. Kolter, D. Langer, O. Pink, V. Pratt, et al. , “Towards fully autonomous driving: Systems and algorithms,” in 2011 IEEE Intelligent Vehicles Symposium (IV) . IEEE, 2011, pp. 163–168
2011
Cited alongside, same era.
T. Shan and B. Englot, “Lego-loam: Lightweight and ground-optimized lidar odometry and mapping on variable terrain,” in 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) . IEEE, 2018, pp. 4758–4765
2018
Later among the works it cites.
F. Gao, W. Wu, W. Gao, and S. Shen, “Flying on point clouds: Online trajectory generation and autonomous navigation for quadrotors in cluttered environments,” Journal of Field Robotics , vol. 36, no. 4, pp. 710–733, 2019
2019
Later among the works it cites.
2019
Later among the works it cites.
H. Ye, Y. Chen, and M. Liu, “Tightly coupled 3d lidar inertial odometry and mapping,” in 2019 International Conference on Robotics and Automation (ICRA) . IEEE, 2019, pp. 3144–3150
2019
Later among the works it cites.
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R. B. Rusu and S. Cousins, “3d is here: Point cloud library (pcl),” in 2011 IEEE international conference on robotics and automation . IEEE, 2011, pp. 1–4
2011
Cited alongside, same era.
R. Newcombe, “Dense visual slam,” Ph.D. dissertation, Imperial College London, 2012
2012
Cited alongside, same era.
M. Kaess, H. Johannsson, R. Roberts, V. Ila, J. J. Leonard, and F. Dellaert, “isam2: Incremental smoothing and mapping using the bayes tree,” The International Journal of Robotics Research , vol. 31, no. 2, pp. 216–235, 2012
2012
Cited alongside, same era.
J. Elseberg, S. Magnenat, R. Siegwart, and A. Nüchter, “Comparison of nearest-neighbor-search strategies and implementations for efficient shape registration,” Journal of Software Engineering for Robotics , vol. 3, no. 1, pp. 2–12, 2012
2012
Cited alongside, same era.
M. Meilland, C. Barat, and A. Comport, “3d high dynamic range dense visual slam and its application to real-time object re-lighting,” in 2013 IEEE International Symposium on Mixed and Augmented Reality (ISMAR) . IEEE, 2013, pp. 143–152
2013
Cited alongside, same era.
C. Kerl, J. Sturm, and D. Cremers, “Dense visual slam for rgb-d cameras,” in 2013 IEEE/RSJ International Conference on Intelligent Robots and Systems . IEEE, 2013, pp. 2100–2106
2013
Cited alongside, same era.
C. Forster, M. Pizzoli, and D. Scaramuzza, “Svo: Fast semi-direct monocular visual odometry,” in 2014 IEEE international conference on robotics and automation (ICRA) . IEEE, 2014, pp. 15–22
2014
Cited alongside, same era.
J. Zhang and S. Singh, “Loam: Lidar odometry and mapping in real-time.” in Robotics: Science and Systems , vol. 2, no. 9, 2014
2014
Cited alongside, same era.
D. Wang, C. Watkins, and H. Xie, “Mems mirrors for lidar: A review,” Micromachines , vol. 11, no. 5, p. 456, 2020
2020
Later among the works it cites.
J. Lin and F. Zhang, “Loam livox: A fast, robust, high-precision lidar odometry and mapping package for lidars of small fov,” in 2020 IEEE International Conference on Robotics and Automation (ICRA) . IEEE, 2020, pp. 3126–3131
2020
Later among the works it cites.
T. Shan, B. Englot, D. Meyers, W. Wang, C. Ratti, and D. Rus, “Lio-sam: Tightly-coupled lidar inertial odometry via smoothing and mapping,” in 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) , 2020, pp. 5135–5142
2020
Later among the works it cites.
C. Qin, H. Ye, C. E. Pranata, J. Han, S. Zhang, and M. Liu, “Lins: A lidar-inertial state estimator for robust and efficient navigation,” in 2020 IEEE International Conference on Robotics and Automation (ICRA) . IEEE, 2020, pp. 8899–8906
2020
Later among the works it cites.
K. Koide, M. Yokozuka, S. Oishi, and A. Banno, “Voxelized gicp for fast and accurate 3d point cloud registration,” EasyChair Preprint , no. 2703, 2020
2020
Later among the works it cites.
Z. Yan, L. Sun, T. Krajnik, and Y. Ruichek, “EU long-term dataset with multiple sensors for autonomous driving,” in Proceedings of the 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) , 2020
2020
Later among the works it cites.
W. Wen, Y. Zhou, G. Zhang, S. Fahandezh-Saadi, X. Bai, W. Zhan, M. Tomizuka, and L.-T. Hsu, “Urbanloco: a full sensor suite dataset for mapping and localization in urban scenes,” in 2020 IEEE International Conference on Robotics and Automation (ICRA) . IEEE, 2020, pp. 2310–2316
2020
Later among the works it cites.
C. Campos, R. Elvira, J. J. G. Rodríguez, J. M. Montiel, and J. D. Tardós, “Orb-slam3: An accurate open-source library for visual, visual–inertial, and multimap slam,” IEEE Transactions on Robotics , 2021
2021
Closest in time.
Z. Liu, F. Zhang, and X. Hong, “Low-cost retina-like robotic lidars based on incommensurable scanning,” IEEE/ASME Transactions on Mechatronics , pp. 1–1, 2021
2021
Closest in time.
K. Li, M. Li, and U. D. Hanebeck, “Towards high-performance solid-state-lidar-inertial odometry and mapping,” IEEE Robotics and Automation Letters , vol. 6, no. 3, pp. 5167–5174, 2021
2021
Closest in time.
H. Wang, C. Wang, and L. Xie, “Lightweight 3-d localization and mapping for solid-state lidar,” IEEE Robotics and Automation Letters , vol. 6, no. 2, pp. 1801–1807, 2021
2021
Closest in time.
Z. Liu and F. Zhang, “Balm: Bundle adjustment for lidar mapping,” IEEE Robotics and Automation Letters , vol. 6, no. 2, pp. 3184–3191, 2021
2021
Closest in time.
W. Xu and F. Zhang, “Fast-lio: A fast, robust lidar-inertial odometry package by tightly-coupled iterated kalman filter,” IEEE Robotics and Automation Letters , pp. 1–1, 2021
2021
Closest in time.
2021
Closest in time.
2021
Closest in time.
2021
Closest in time.