Fetching the paper…
Reading the bibliography…
Ego-motion estimation is a fundamental requirement for most mobile robotic applications.
S. Umeyama, “Least-squares estimation of transformation parameters between two point patterns,” IEEE Transactions on Pattern Analysis & Machine Intelligence , no. 4, pp. 376–380, 1991
1991
Earlier work this paper cites.
A. Soloviev, D. Bates, and F. Van Graas, “Tight coupling of laser scanner and inertial measurements for a fully autonomous relative navigation solution,” Navigation , vol. 54, no. 3, pp. 189–205, 2007
2007
Earlier work this paper cites.
M. Bosse and R. Zlot, “Continuous 3d scan-matching with a spinning 2d laser,” in Robotics and Automation, 2009. ICRA’09. IEEE International Conference on . IEEE, 2009, pp. 4312–4319
2009
Earlier work this paper cites.
E. S. Jones and S. Soatto, “Visual-inertial navigation, mapping and localization: A scalable real-time causal approach,” The International Journal of Robotics Research , vol. 30, no. 4, pp. 407–430, 2011
2011
Earlier work this paper cites.
S. Lynen, M. W. Achtelik, S. Weiss, M. Chli, and R. Siegwart, “A robust and modular multi-sensor fusion approach applied to mav navigation,” in Intelligent Robots and Systems (IROS), 2013 IEEE/RSJ International Conference on . IEEE, 2013, pp. 3923–3929
2013
Earlier work this paper cites.
M. Li, B. H. Kim, and A. I. Mourikis, “Real-time motion tracking on a cellphone using inertial sensing and a rolling-shutter camera,” in Robotics and Automation (ICRA), 2013 IEEE International Conference on . IEEE, 2013, pp. 4712–4719
2013
Earlier work this paper cites.
J. Zhang and S. Singh, “Loam: Lidar odometry and mapping in real-time.” in Robotics: Science and Systems , vol. 2, 2014
2014
Cited alongside, same era.
J. Tang, Y. Chen, X. Niu, L. Wang, L. Chen, J. Liu, C. Shi, and J. Hyyppä, “Lidar scan matching aided inertial navigation system in gnss-denied environments,” Sensors , vol. 15, no. 7, pp. 16 710–16 728, 2015
2015
Cited alongside, same era.
S. Leutenegger, S. Lynen, M. Bosse, R. Siegwart, and P. Furgale, “Keyframe-based visual–inertial odometry using nonlinear optimization,” The International Journal of Robotics Research , vol. 34, no. 3, pp. 314–334, 2015
2015
Cited alongside, same era.
G. Hemann, S. Singh, and M. Kaess, “Long-range gps-denied aerial inertial navigation with lidar localization,” in Intelligent Robots and Systems (IROS), 2016 IEEE/RSJ International Conference on . IEEE, 2016, pp. 1659–1666
2016
Cited alongside, same era.
T. Lowe, S. Kim, and M. Cox, “Complementary perception for handheld slam,” IEEE Robotics and Automation Letters , vol. 3, no. 2, pp. 1104–1111, 2018
2018
Later among the works it cites.
T. Qin, P. Li, and S. Shen, “Vins-mono: A robust and versatile monocular visual-inertial state estimator,” IEEE Transactions on Robotics , vol. 34, no. 4, pp. 1004–1020, 2018
2018
Later among the works it cites.
J. Behley and C. Stachniss, “Efficient surfel-based slam using 3d laser range data in urban environments,” in Proc. of Robotics: Science and Systems (RSS) , 2018
2018
Later among the works it cites.
S. Agarwal, K. Mierle, and Others, “Ceres Solver,” (accessed 22-Aug-2018). [Online]. Available: http://ceres-solver.org
2018
Later among the works it cites.
F. Zheng, H. Tang, and Y.-H. Liu, “Odometry-vision-based ground vehicle motion estimation with se (2)-constrained se (3) poses,” IEEE Transactions on Cybernetics , 2018
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
R. Mur-Artal and J. D. Tardós, “Visual-inertial monocular slam with map reuse,” IEEE Robotics and Automation Letters , vol. 2, no. 2, pp. 796–803, 2017
2017
Cited alongside, same era.
C. Park, P. Moghadam, S. Kim, A. Elfes, C. Fookes, and S. Sridharan, “Elastic lidar fusion: Dense map-centric continuous-time slam,” in 2018 IEEE International Conference on Robotics and Automation (ICRA) . IEEE, 2018, pp. 1206–1213
2018
Cited alongside, same era.
H. Ye, Y. Chen, and M. Liu, “Supplementary material to: Tightly coupled 3d lidar inertial odometry and mapping,” Tech. Rep. [Online]. Available: https://sites.google.com/view/lio-mapping
Cited in the paper.
2018
Later among the works it cites.
J. Jeong, Y. Cho, Y.-S. Shin, H. Roh, and A. Kim, “Complex urban lidar data set,” in 2018 IEEE International Conference on Robotics and Automation (ICRA) . IEEE, 2018, pp. 6344–6351
2018
Later among the works it cites.