The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Autonomous Navigation Using Monocular ORB SLAM2
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Integrity signals
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Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“Recently, SLAM has become a critical enabling technology for many emerging human-centered applications, such as AR/VR [45], HD map [6], [46], and autonomous navigation [47].”
From Orchestrating Joint Offloading and Scheduling for Low-Latency Edge SLAM (2025) · cites this paper as [45]
Citations
Cites
Strasdat, H., Montiel, J. M. M., & Davison, A. J. (2012) · Image and Vision Computing · doi:10.1016/j.imavis.2012.02.009 · Cited by 439
Flagged first, then by citations
Research works printed but not linked: 12
- Mur-Artal, Raul, and Juan D. Tardós. 2017. ORB-SLAM2: An Open-Source SLAM System for Monocular, Stereo, and RGB-D Cameras. IEEE Transactions on Robotics 33: 1255–1262. · DOI · Paper page
- Koenig, Nathan P., and Andrew G. Howard. 2004. Design and Use Paradigms for Gazebo, An Open-Source Multi-Robot Simulator. In 2004 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (IEEE Cat. No.04CH37566) 3, 2149–2154.
- Biswas, Joydeep, and Manuela M. Veloso. 2012. Depth camera based indoor mobile robot localization and navigation. In 2012 IEEE International Conference on Robotics and Automation 1697–1702. · DOI
- Gatesichapakorn, Sukkpranhachai, et al. 2019. ROS Based Autonomous Mobile Robot Navigation Using 2D LiDAR and RGB-D Camera. In 2019 First International Symposium on Instrumentation, Control, Artificial Intelligence, and Robotics (ICA-SYMP) 151–154.
- Weingarten, Jan W., and Roland Siegwart. 2005. EKF-Based 3D SLAM for Structured Environment Reconstruction. In 2005 IEEE/RSJ International Conference on Intelligent Robots and Systems 3834–3839. · DOI
- Cheng, Jiantong, et al. 2014. Compressed Unscented Kalman Filter-Based SLAM. In 2014 IEEE International Conference on Robotics and Biomimetics (ROBIO 2014) 1602–1607. · DOI
- Törnqvist, David, et al. 2009. Particle Filter SLAM With High Dimensional Vehicle Model. Journal of Intelligent and Robotic Systems 55: 249–266. · DOI
- Montemerlo, Michael, et al. 2002. FastSLAM: A Factored Solution to the Simultaneous Localization and Mapping Problem. AAAI/IAAI.
- Triggs, Bill, et al. 1999. Bundle Adjustment—A Modern Synthesis. Workshop on Vision Algorithms. · DOI · Paper page
- Klein, Georg, and David William Murray. 2007. Parallel Tracking and Mapping for Small AR Workspaces. In 2007 6th IEEE and ACM International Symposium on Mixed and Augmented Reality 225–234. · DOI · Paper page
- Izadi, Shahram, et al. 2011. Kinect Fusion: Real-Time 3D Reconstruction and Interaction Using a Moving Depth Camera. UIST. · DOI
- Rublee, Ethan, et al. 2011. ORB: An Efficient Alternative to SIFT or SURF. In 2011 International Conference on Computer Vision 2564–2571. · DOI · Paper page
Cited by
Sorted by citations
Orchestrating Joint Offloading and Scheduling for Low-Latency Edge SLAM
Zhang, Y., Mao, Y., Wang, H., Yu, Z., Guo, S., Zhang, J., Wang, L., & Guo, B. (2025) · IEEE Transactions on Mobile Computing · doi:10.1109/tmc.2025.3547256 · Cited by 1
“Recently, SLAM has become a critical enabling technology for many emerging human-centered applications, such as AR/VR [45], HD map [6], [46], and autonomous navigation [47].”
Metadata
- Authors
- Vithalani, S., Soni, S., & Rajpura, P.
- Affiliations
- Nirma University (IN)
- Corresponding author
- Vithalani, Shubham
- Venue
- Lecture Notes in Electrical Engineering
- Publisher
- Springer Singapore
- Published
- 2019-11-13
- Pages
- 59-68
- ISSN
- 1876-1100 (ISSN-L)
- 1876-1119
- OpenAlex
- W2984929584
- Cited by
- 4
- References
- 1
- Citations by year
- 2025: 2 · 2023: 1 · 2020: 1
- FWCI
- 0.92
- Type
- book chapter
- Language
- en
- Open access
- closed
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Lecture notes in electrical engineering (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Robotics and Sensor-Based Localization
- Physical Sciences › Engineering › Control and Systems Engineering › Robotic Path Planning Algorithms
- Physical Sciences › Computer Science › Artificial Intelligence › Reinforcement Learning in Robotics
- Keywords
- autonomous navigation, monocular SLAM, ORB-SLAM2, visual SLAM, scale drift, A* path planning, local path planning, Turtlebot, differential drive robot, robot localization, robot simulation
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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