EDP Sciences logo
Submit your paper
Search
Menu
All issues Volume 28 / No 1 (February 2023) Wuhan Univ. J. Nat. Sci., 28 1 (2023) 20-28 References
Open Access
Issue
Wuhan Univ. J. Nat. Sci.
Volume 28, Number 1, February 2023
Page(s) 20 - 28
DOI https://doi.org/10.1051/wujns/2023281020
Published online 17 March 2023
  1. Lei L, Li Z H, Yang H, et al. Extraction of the leaf area density of maize using UAV-LiDAR data [J]. Geomatics and Information Science of Wuhan University, 2021, 46(11): 1737-1745(Ch). [Google Scholar]
  2. Chen J J, Li S, Liu D H, et al. AiRobSim: Simulating a multisensor aerial robot for urban search and rescue operation and training [J]. Sensors (Basel, Switzerland), 2020, 20(18): 5223. [NASA ADS] [CrossRef] [PubMed] [Google Scholar]
  3. Tabib W, Goel K, Yao J, et al. Autonomous cave surveying with an aerial robot [EB/OL].[2022-06-25]. https://arxiv.org/abs/2003.13883. [Google Scholar]
  4. Geneva P, Eckenhoff K, Lee W, et al. OpenVINS: A research platform for visual-inertial estimation [C]// 2020 IEEE International Conference on Robotics and Automation (ICRA). New York: IEEE, 2020: 4666-4672. [Google Scholar]
  5. Paul M K, Roumeliotis S I. Alternating-stereo VINS: Observability analysis and performance evaluation [C]//2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition. New York: IEEE, 2018: 4729-4737. [Google Scholar]
  6. Qin T, Li P L, Shen S J. VINS-mono: A robust and versatile monocular visual-inertial state estimator [J]. IEEE Transactions on Robotics, 2018, 34(4): 1004-1020. [CrossRef] [Google Scholar]
  7. Rosinol A, Abate M, Chang Y, et al. Kimera: An open-source library for real-time metric-semantic localization and mapping [C]// 2020 IEEE International Conference on Robotics and Automation (ICRA). New York: IEEE, 2020: 1689-1696. [Google Scholar]
  8. Campos C, Elvira R, Rodríguez J J G, et al. ORB-SLAM3: An accurate open-source library for visual, visual-inertial, and multimap SLAM [J]. IEEE Transactions on Robotics, 2021, 37(6): 1874-1890. [CrossRef] [Google Scholar]
  9. Mur-Artal R, Montiel J M M, Tardós J D. ORB-SLAM: A versatile and accurate monocular SLAM system [J]. IEEE Transactions on Robotics, 2015, 31(5): 1147-1163. [CrossRef] [Google Scholar]
  10. Mur-Artal R, Tardós J D. ORB-SLAM2: An open-source SLAM system for monocular, stereo, and RGB-D cameras [J]. IEEE Transactions on Robotics, 2017, 33(5): 1255-1262. [CrossRef] [Google Scholar]
  11. Li T, Zhang H P, Gao Z Z, et al. Tight fusion of a monocular camera, MEMS-IMU, and single-frequency multi-GNSS RTK for precise navigation in GNSS-challenged environments [J]. Remote Sensing, 2019, 11(6): 610. [NASA ADS] [CrossRef] [Google Scholar]
  12. Cao S Z, Lu X Y, Shen S J. GVINS: Tightly coupled GNSS-visual-inertial fusion for smooth and consistent state estimation [J]. IEEE Transactions on Robotics, 2022, 38(4): 2004-2021. [CrossRef] [Google Scholar]
  13. Zhang C, Yang Z, Fang Q H, et al. FRL-SLAM: A fast, robust and lightweight SLAM system for quadruped robot navigation [C]//2021 IEEE International Conference on Robotics and Biomimetics (ROBIO). New York: IEEE, 2022: 1165-1170. [Google Scholar]
  14. Zhang C, Yang Z, Liao L W, et al. RPEOD: A real-time pose estimation and object detection system for aerial robot target tracking [J]. Machines, 2022, 10(3): 181. [CrossRef] [MathSciNet] [Google Scholar]
  15. Lucas B D, Kanade T. An iterative image registration technique with an application to stereo vision [C]// Proceedings of the 7th International Joint Conference on Artificial Intelligence. New York: ACM, 1981: 674-679. [Google Scholar]
  16. Shi J B, Tomasi. Good features to track [C]//1994 Proceedings of IEEE Conference on Computer Vision and Pattern Recognition. New York: IEEE, 2002: 593-600. [Google Scholar]
  17. Leutenegger S, Lynen S, Bosse M, et al. Keyframe-based visual-inertial odometry using nonlinear optimization [J]. The International Journal of Robotics Research, 2015, 34(3): 314-334. [CrossRef] [Google Scholar]
  18. Forster C, Pizzoli M, Scaramuzza D. SVO: Fast semi-direct monocular visual odometry [C]// 2014 IEEE International Conference on Robotics and Automation (ICRA). New York: IEEE, 2014: 15-22. [Google Scholar]
  19. Engel J, Schöps T, Cremers D. LSD-SLAM: Large-scale direct monocular SLAM [C]// Proceedings of the European Conference on Computer Vision (ECCV). Berlin: Springer, 2014: 834-849. [Google Scholar]
  20. Qin T, Li P L, Shen S J. Relocalization, global optimization and map merging for monocular visual-inertial SLAM [C]// 2018 IEEE International Conference on Robotics and Automation (ICRA). New York: IEEE, 2018: 1197-1204. [Google Scholar]
  21. Qin T, Shen S J. Robust initialization of monocular visual-inertial estimation on aerial robots [C]//2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). New York: IEEE, 2017: 4225-4232. [Google Scholar]
  22. Burri M, Nikolic J, Gohl P, et al. The EuRoC micro aerial vehicle datasets [J]. The International Journal of RoboticsResearch, 2016, 35(10): 1157-1163. □ [CrossRef] [Google Scholar]

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.