On the Consistency of Vision-Aided Inertial Navigation
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The performance mismatch between filtering and MAP estimation gets smaller when the linearization point for the EKF is accurate, when using sliding-window filters, and when potential sources of inconsistency in the EKF are taken care of.
“Not surprisingly, the performance mismatch between filtering and MAP estimation gets smaller when the linearization point for the EKF is accurate (as it happens in visual-inertial navigation problems), when using slidingwindow filters, and when potential sources of inconsistency in the EKF are taken care of [105, 108, 139].”
From Past, Present, and Future of Simultaneous Localization and Mapping: Toward the Robust-Perception Age (2016) · cites this paper as [139]
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Nonlinear controllability and observability
Hermann, R., & Krener, A. (1977) · IEEE Transactions on Automatic Control · doi:10.1109/tac.1977.1101601 · Cited by 2,374 · cited 1× · see citing works
“For the task of IMU-camera extrinsic calibration, Mirzaei and Roumeliotis [19], as well as Kelly and Sukhatme [15], have analyzed the system observability using Lie derivatives [7] to determine when the IMU-camera transformation is observable.”
MethodVision-Aided Inertial Navigation for Spacecraft Entry, Descent, and Landing
Mourikis, A. I., Trawny, N., Roumeliotis, S. I., Johnson, A. E., Ansar, A., & Matthies, L. (2009) · IEEE Transactions on Robotics · doi:10.1109/tro.2009.2012342 · Cited by 345 · see citing works
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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 · see citing works
On-Manifold Preintegration for Real-Time Visual--Inertial Odometry
Forster, C., Carlone, L., Dellaert, F., & Scaramuzza, D. (2017) · IEEE Transactions on Robotics · doi:10.1109/tro.2016.2597321 · Cited by 1,502 · see citing works
High-precision, consistent EKF-based visual-inertial odometry
Li, M., & Mourikis, A. I. (2013) · The International Journal of Robotics Research · doi:10.1177/0278364913481251 · Cited by 813 · see citing works
Klingensmith, M., Dryanovski, I., Srinivasa, S., & Xiao, J. (2015) · Robotics: Science and Systems XI · doi:10.15607/rss.2015.xi.040 · Cited by 163 · see citing works
- Authors
- Kottas, D. G., Hesch, J. A., Bowman, S. L., & Roumeliotis, S. I.
- Affiliations
- University of Minnesota (US)
- Corresponding author
- Kottas, Dimitrios G.
- Venue
- Springer Tracts in Advanced Robotics
- Publisher
- Springer International Publishing
- Published
- 2013
- Pages
- 303-317
- ISSN
- 1610-742X (ISSN-L)
- 1610-7438
- OpenAlex
- W956540729
- Cited by
- 76
- References
- 2
- Citations by year
- 2023: 4 · 2022: 4 · 2021: 2 · 2020: 6 · 2019: 9 · 2018: 7 · 2017: 6 · 2016: 11 · 2015: 6 · 2014: 10 · 2013: 9 · 2012: 2
- FWCI
- 31.89
- Type
- book chapter
- Language
- en
- Open access
- closed
- Licence
- Locations
- Springer tracts in advanced robotics (publishedVersion)
- Topics
- Physical Sciences › Engineering › Aerospace Engineering › Inertial Sensor and Navigation
- Physical Sciences › Engineering › Aerospace Engineering › Robotics and Sensor-Based Localization
- Physical Sciences › Computer Science › Artificial Intelligence › Target Tracking and Data Fusion in Sensor Networks
- Keywords
- vision-aided inertial navigation, estimator inconsistency, observability, extended Kalman filter, multi-state constraint Kalman filter, state estimation
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