The DOI matches its Crossref record; 14 of the 14 references it cites were found in a registry or an index.
Consistency of the EKF-SLAM Algorithm
Abstract
This paper presents an analysis of the extended Kalman filter formulation of simultaneous localisation and mapping (EKF-SLAM). We show that the algorithm produces very optimistic estimates once the "true" uncertainty in vehicle heading exceeds a limit. This failure is subtle and cannot, in general, be detected without ground-truth, although a very inconsistent filter may exhibit observable symptoms, such as disproportionately large jumps in the vehicle pose update. Conventional solutions - adding stabilising noise, using an iterated EKF or unscented filter, etc., - do not improve the situation. However, if "small" heading uncertainty is maintained, EKF-SLAM exhibits consistent behaviour over an extended time-period. Although the uncertainty estimate slowly becomes optimistic, inconsistency can be mitigated indefinitely by applying tactics such as batch updates or stabilising noise. The manageable degradation of small heading variance SLAM indicates the efficacy of submap methods for large-scale maps
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Citations
Cites
Estimation with Applications to Tracking and Navigation: Theory, Algorithms and Software
Bar‐Shalom, Y., Li, X. ‐., & Kirubarajan, T. (2002) · doi:10.1002/0471221279 · Cited by 6,782
A new method for the nonlinear transformation of means and covariances in filters and estimators
Julier, S., Uhlmann, J., & Durrant-Whyte, H. F. (2000) · IEEE Transactions on Automatic Control · doi:10.1109/9.847726 · Cited by 3,735
A solution to the simultaneous localization and map building (SLAM) problem
Dissanayake, M. W. M. G., Newman, P., Clark, S., Durrant-Whyte, H. F., & Csorba, M. (2001) · IEEE Transactions on Robotics and Automation · doi:10.1109/70.938381 · Cited by 2,661
Montemerlo, M., Thrun, S., Roller, D., & Wegbreit, B. (2003) · International Joint Conference on Artificial Intelligence · Cited by 868
Incremental mapping of large cyclic environments
Gutmann, J.-S., & Konolige, K. (2003) · Proceedings 1999 IEEE International Symposium on Computational Intelligence in Robotics and Automation. CIRA'99 (Cat. No.99EX375) · doi:10.1109/cira.1999.810068 · Cited by 568
A stochastic map for uncertain spatial relationships
Smith, R. K., Self, M. W., & Cheeseman, P. C. (1988) · Cited by 425
A counter example to the theory of simultaneous localization and map building
Julier, S. J., & Uhlmann, J. K. (2002) · Proceedings 2001 ICRA. IEEE International Conference on Robotics and Automation (Cat. No.01CH37164) · doi:10.1109/robot.2001.933280 · Cited by 317
An Atlas framework for scalable mapping
Bosse, M., Newman, P., Leonard, J., Soika, M., Feiten, W., & Teller, S. (2003) · 2003 IEEE International Conference on Robotics and Automation (Cat. No.03CH37422) · doi:10.1109/robot.2003.1241872 · Cited by 313
Limits to the consistency of EKF-based SLAM
Castellanos, J. A., Neira, J., & Tardós, J. D. (2004) · IFAC Proceedings Volumes · doi:10.1016/s1474-6670(17)32063-3 · Cited by 239
Efficient Solutions to Autonomous Mapping and Navigation Problems
Williams, S. B. (2009) · The Sydney eScholarship Repository (The University of Sydney) · Cited by 147
Cited by
Simultaneous Localization and Mapping: A Survey of Current Trends in Autonomous Driving
Bresson, G., Alsayed, Z., Yu, L., & Glaser, S. (2017) · IEEE Transactions on Intelligent Vehicles · doi:10.1109/tiv.2017.2749181 · Cited by 885
Simultaneous Localization and Mapping
Thrun, S. (2007) · Springer Tracts in Advanced Robotics · doi:10.1007/978-3-540-75388-9_3 · Cited by 530
6D SLAM—3D mapping outdoor environments
Nüchter, A., Lingemann, K., Hertzberg, J., & Surmann, H. (2007) · Journal of Field Robotics · doi:10.1002/rob.20209 · Cited by 450
Observability-based Rules for Designing Consistent EKF SLAM Estimators
Huang, G. P., Mourikis, A. I., & Roumeliotis, S. I. (2010) · The International Journal of Robotics Research · doi:10.1177/0278364909353640 · Cited by 272
Mapping forests using an unmanned ground vehicle with 3D LiDAR and graph-SLAM
Pierzchała, M., Giguère, P., & Astrup, R. (2018) · Computers and Electronics in Agriculture · doi:10.1016/j.compag.2017.12.034 · Cited by 258
Metadata
- Authors
- Bailey, T., Nieto, J., Guivant, J., Stevens, M., & Nebot, E.
- Venue
- 2006 IEEE/RSJ International Conference on Intelligent Robots and Systems
- Publisher
- IEEE
- Published
- 2006-10
- Pages
- 3562-3568
- OpenAlex
- W2165468899
- Cited by
- 566
- References
- 14
- FWCI
- 55.46
- Type
- conference paper
- Language
- en
- Open access
- closed
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- Bailey, T., Nieto, J., Guivant, J., Stevens, M., & Nebot, E. (2006). Consistency of the EKF-SLAM Algorithm. 2006 IEEE/RSJ International Conference on Intelligent Robots and Systems. https://doi.org/10.1109/iros.2006.281644
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