Jianxian Cai, Penggang Gao, Yanxiong Wu, and Zhitao Gao


  1. [1] M. Lemmens, Global navigation satellite systems and inertialnavigation Geo-information (Netherland: Springer, 2011),55–83.
  2. [2] J. Fuentes-Pacheco, J. Ruiz-Ascencio, J.M. Rend´on-Mancha,Visual simultaneous localization and mapping: a survey, Arti-ficial intelligence review, 43(1), 2015, 55–81.
  3. [3] R. Mur-Artal and J.D. Tard´os, Orb-slam2: An open-sourceslam system for monocular, stereo, and RGB-D cameras, IEEETransactions on Robotics, 33(5), 2017, 1255–1262.39
  4. [4] R. Gomez-Ojeda, F.A. Moreno, D. Zu˜niga-No¨el, et al., PL-SLAM: A stereo SLAM system through the combination ofpoints and line segments, IEEE Transactions on Robotics,35(3), 2019, 734–746.
  5. [5] L. Hu, W. Xu, K. Huang, et al., Deep-SLAM++: Object-level RGBD SLAM based on class-specific deep shape priors,arXiv:1907.09691, 2019.
  6. [6] M. Schaerf, M. Mecella, D.V. Igorevna, K.I. Anatolievich (eds.):Proceedings of REMS 2018 – Russian Federation & EuropeMultidisciplinary Symposium on Computer Science and ICT,Stavropol – Dombay, Russia, 15–20 October 2018, publishedat
  7. [7] M. Burri, H. Oleynikova, M.W. Achtelik, and R. Siegwart,Real-time visual-inertial mapping, re-localization and planningonboard MAVs in unknown environment, IEEE/RSJ Int. Conf.on Intelligent Robots and Systems, Hamburg, Germany, 2015,1872–1878.
  8. [8] U. Qayyum, Q. Ahsan, and Z. Mahmood, IMU aided RGB-DSLAM, Int. Bhurban Conf. on Applied Sciences and Technology,Islamabad, Pakistan, 2017, 337–341.
  9. [9] Z. Shan, R. Li, and S. Schwertfeger, RGBD-inertial trajectoryestimation and mapping for ground robots, Sensors, 19(10),2019, 2251.
  10. [10] A.I. Mourikis and S.I. Roumeliotis, A multi-state constraintKalman filter for vision-aided inertial navigation, 2007 IEEEInt. Conf. on Robotics and Automation, Roma, Italy, 2007,3565–3572.
  11. [11] M. Bloesch, S. Omari, M. Hutter, et al., Robust visual inertialodometry using a direct EKF-based approach, 2015 IEEE/RSJInt. Conf. on Intelligent Robots and Systems (IROS), Hamburg,Germany, 2015, 298–304.
  12. [12] S. Lynen, M.W. Achtelik, S. Weiss, et al., A robust and mod-ular multi-sensor fusion approach applied to MAV navigation,2013 IEEE/RSJ Int. Conf. on Intelligent Robots and Systems(IROS), Tokyo, Japan, 2013, 3923–3929.
  13. [13] J.M. Falquez, M. Kasper, and G. Sibley, Inertial aided denseand semi-dense methods for robust direct visual odometry,2016 IEEE/RSJ Int. Conf. on Intelligent Robots and Systems(IROS), Daejeon, Korea, 2016, 3601–3607.
  14. [14] S. Leutenegger, S. Lynen, M. Bosse, et al., Keyframe-basedvisual–inertial odometry using nonlinear optimization, The In-ternational Journal of Robotics Research, 34(3), 2015, 314–334.
  15. [15] R. Mur-Artal and J.D. Tard´os, Orb-slam2: An open-sourceslam system for monocular, stereo, and rgb-d cameras, IEEETransactions on Robotics, 33(5), 2017, 1255–1262.
  16. [16] C. Forster, L. Carlone, F. Dellaert, et al., On-manifoldpreintegration for real-time visual—inertial odometry, IEEETransactions on Robotics, 33(1), 2017, 1–21.
  17. [17] T. Qin, P. Li, and S. Shen, Vins-mono: A robust and versatilemonocular visual-inertial state estimator, IEEE Transactionson Robotics, 34(4), 2018, 1004–1020.
  18. [18] M. Keller, F. Hoffmann, C. Hass, et al., Planning of optimalcollision avoidance trajectories with timed elastic bands, IFACProceedings Volumes, 47(3), 2014, 9822–9827.
  19. [19] J. Kim and J.P. Ostrowski, Motion planning a aerial robotusing rapidly-exploring random trees with dynamic con-straints, IEEE Int. Conf. on Robotics and Automation, Proc.of ICRA, Kongresszentrum Karlsruhe, Karlsruhe, Germany,2003, 2200–2205.
  20. [20] L.H. Thomas, Elliptic problems in linear difference equationsover a network, Watson Scientific Computing LaboratoryReport, Columbia University, New York, 1949.
  21. [21] J. Engel, T. Sch¨ops, and D. Cremers, LSD-SLAM: Large-scaledirect monocular SLAM, Computer Vision – ECCV 2014(Berlin: Springer International Publishing, 2014), Zurich,Switzerland, 834–849.
  22. [22] M. Kok, J.D. Hol and T.B. Sch¨on, Using Inertial Sen-sors for position and orientation estimation, Founda-tions and Trends in Signal Processing, 11(1–2), 1–153.
  23. [23] L.K. Bieniasz, Extension of the Thomas algorithm to a classof algebraic linear equation systems involving quasi-block-tridiagonal matrices with isolated block-pentadiagonal rows,assuming variable block dimensions, Computing, 67(4), 2001,269–285.
  24. [24] M. Quigley, K. Conley, B. Gerkey, et al., ROS: An open-sourcerobot operating system, ICRA Workshop on Open SourceSoftware, Kobe, Japan, 2009, 5.

Important Links:

Go Back