The DOI matches its Crossref record; 36 of the 37 references it cites were found in a registry or an index.
Initialization techniques for 3D SLAM: A survey on rotation estimation and its use in pose graph optimization
Abstract
Pose graph optimization is the non-convex optimization problem underlying pose-based Simultaneous Localization and Mapping (SLAM). If robot orientations were known, pose graph optimization would be a linear least-squares problem, whose solution can be computed efficiently and reliably. Since rotations are the actual reason why SLAM is a difficult problem, in this work we survey techniques for 3D rotation estimation. Rotation estimation has a rich history in three scientific communities: robotics, computer vision, and control theory. We review relevant contributions across these communities, assess their practical use in the SLAM domain, and benchmark their performance on representative SLAM problems (Fig. 1). We show that the use of rotation estimation to bootstrap iterative pose graph solvers entails significant boost in convergence speed and robustness.
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“State-of-the-art iterative solvers fail to converge to a global minimum of the cost for relatively small noise levels [32, 37].”
From Past, Present, and Future of Simultaneous Localization and Mapping: Toward the Robust-Perception Age (2016) · cites this paper as [37]
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Distributed Control of Robotic Networks
Bullo, F., Cortés, J., & Martínez, S. (2009) · Princeton University Press eBooks · doi:10.1515/9781400831470 · Cited by 1,538
Distributed Control of Robotic Networks
Bullo, F. (2009) · Cited by 591
Factor Graphs and GTSAM: A Hands-on Introduction
Dellaert, F. (2012) · SMARTech Repository (Georgia Institute of Technology) · Cited by 583
Self-citationHartley, R. I., Trumpf, J., Dai, Y., & Li, H. (2013) · International Journal of Computer Vision · doi:10.1007/s11263-012-0601-0 · Cited by 529
Fast iterative alignment of pose graphs with poor initial estimates
Olson, E., Leonard, J., & Teller, S. (2006) · Proceedings 2006 IEEE International Conference on Robotics and Automation, 2006. ICRA 2006. · doi:10.1109/robot.2006.1642040 · Cited by 427
Robust Rotation and Translation Estimation in Multiview Reconstruction
Martinec, D., & Pajdla, T. (2007) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2007.383115 · Cited by 323
Martinelli, A. (2011) · IEEE Transactions on Robotics · doi:10.1109/tro.2011.2160468 · Cited by 283
Consensus Optimization on Manifolds
Sarlette, A., & Sepulchre, R. J. (2009) · SIAM Journal on Control and Optimization · doi:10.1137/060673400 · Cited by 268
Lie-algebraic averaging for globally consistent motion estimation
Govindu, V. M. (2004) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2004.1315098 · Cited by 256
Efficient and Robust Large-Scale Rotation Averaging
Chatterjee, A., & Govindu, V. M. (2013) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2013.70 · Cited by 232
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Past, Present, and Future of Simultaneous Localization and Mapping: Toward the Robust-Perception Age
Cadena, C., Carlone, L., Carrillo, H., Latif, Y., Scaramuzza, D., Neira, J., Reid, I., & Leonard, J. J. (2016) · IEEE Transactions on Robotics · doi:10.1109/tro.2016.2624754 · Cited by 3,596
Self-citationPast, present, and future of simultaneous localization and mapping: Toward the robust-perception age
Cadena, C., Carlone, L., Carrillo, H., Latif, Y., Scaramuzza, D., Neira, J., Reid, I. D., & Leonard, J. J. (2016) · Zurich Open Repository and Archive (University of Zurich) · doi:10.5167/uzh-138892 · Cited by 3,094
Self-citationSE-Sync: A certifiably correct algorithm for synchronization over the special Euclidean group
Rosen, D. M., Carlone, L., Bandeira, A. S., & Leonard, J. J. (2018) · The International Journal of Robotics Research · doi:10.1177/0278364918784361 · Cited by 303
Self-citationGlobal Structure-from-Motion by Similarity Averaging
Cui, Z., & Tan, P. (2015) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2015.105 · Cited by 160
Very Large-Scale Global SfM by Distributed Motion Averaging
Zhu, S., Zhang, R., Zhou, L., Shen, T., Fang, T., Tan, P., & Quan, L. (2018) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2018.00480 · Cited by 155
Metadata
- Authors
- Carlone, L., Tron, R., Daniilidis, K., & Dellaert, F.
- Affiliations
- Georgia Institute of Technology (US)
- University of Pennsylvania (US)
- Venue
- 2015 IEEE International Conference on Robotics and Automation (ICRA)
- Publisher
- IEEE
- Published
- 2015-05
- Pages
- 4597-4604
- ISSN
- 1050-4729 (ISSN-L)
- OpenAlex
- W1536617987
- Cited by
- 237
- References
- 37
- Citations by year
- 2026: 11 · 2025: 17 · 2024: 17 · 2023: 29 · 2022: 24 · 2021: 31 · 2020: 29 · 2019: 22 · 2018: 27 · 2017: 14 · 2016: 11 · 2015: 5
- FWCI
- 32.95
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- Proceedings - IEEE International Conference on Robotics and Automation/Proceedings (publishedVersion)
- SMARTech Repository (Georgia Institute of Technology) (submittedVersion)
- Topics
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Robotics and Sensor-Based Localization
- Physical Sciences › Computer Science › Artificial Intelligence › Target Tracking and Data Fusion in Sensor Networks
- Physical Sciences › Engineering › Aerospace Engineering › Inertial Sensor and Navigation
- Keywords
- 3D rotation estimation, pose graph optimization, SLAM, non-convex optimization, robot orientation, convergence rate, robustness
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