Skip to main content

Main menu

  • Home
  • Current Issue
  • Archive
  • About Us
    • About NAVIGATION
    • Editorial Board
    • Peer Review Statement
    • Open Access
  • More
    • Email Alerts
    • Info for Authors
    • Info for Subscribers
  • Other Publications
    • ion

User menu

  • My alerts

Search

  • Advanced search
NAVIGATION: Journal of the Institute of Navigation
  • Other Publications
    • ion
  • My alerts
NAVIGATION: Journal of the Institute of Navigation

Advanced Search

  • Home
  • Current Issue
  • Archive
  • About Us
    • About NAVIGATION
    • Editorial Board
    • Peer Review Statement
    • Open Access
  • More
    • Email Alerts
    • Info for Authors
    • Info for Subscribers
  • Follow ion on Twitter
  • Visit ion on Facebook
  • Follow ion on Instagram
  • Visit ion on YouTube
Research ArticleOriginal Article
Open Access

Accurate Covariance Estimation for Pose Data From Iterative Closest Point Algorithm

Rick H. Yuan, Clark N. Taylor, and Scott L. Nykl
NAVIGATION: Journal of the Institute of Navigation June 2023, 70 (2) navi.562; DOI: https://doi.org/10.33012/navi.562
Rick H. Yuan
Electrical and Computer Engineering, Air Force Institute of Technology, Ohio, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Clark N. Taylor,
Electrical and Computer Engineering, Air Force Institute of Technology, Ohio, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • For correspondence: [email protected] [email protected]
Scott L. Nykl
Electrical and Computer Engineering, Air Force Institute of Technology, Ohio, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • Article
  • Figures & Data
  • Supplemental
  • References
  • Info & Metrics
  • PDF
Loading

REFERENCES

  1. ↵
    1. Anderson, J.,
    2. Miller, J.,
    3. Wu, X.,
    4. Nykl, S.,
    5. Taylor, C., &
    6. Watkinson, W.
    (2021, August). Real-time automated aerial refueling with stereo vision: overcoming GNSS-denied environments in or near combat areas. Inside GNSS. https://insidegnss.com/real-time-automated-aerial-refueling-with-stereo-vision-overcoming-gnss-denied-environments-in-or-near-combat-areas
  2. ↵
    1. Arun, K. S.,
    2. Huang, T. S., &
    3. Blostein, S. D.
    (1987). Least-squares fitting of two 3D point sets. IEEE Transactions on Pattern Analysis and Machine Intelligence, PAMI-9(5), 698–700. Retrieved from https://doi.org/10.1109/tpami.1987.4767965
    CrossRefPubMedWeb of Science
  3. ↵
    1. Besl, P. J., &
    2. McKay, N. D.
    (1992). A method for registration of 3D shapes. IEEE Transactions on Pattern Analysis and Machine Intelligence, 14(2), 239–256. https://doi.org/10.1109/34.121791
    CrossRefWeb of Science
  4. ↵
    1. Brossard, M.,
    2. Bonnabel, S., &
    3. Barrau, A.
    (2020). A new approach to 3D ICP covariance estimation. IEEE Robotics and Automation Letters, 5(2), 744–751. https://doi.org/10.1109/lra.2020.2965391
  5. ↵
    1. Censi, A.
    (2007). An accurate closed-form estimate of ICP’s covariance. Proc. 2007 IEEE International Conference on Robotics and Automation, Rome, Italy, 3167–3172. http://doi.org/10.1109/ROBOT.2007.363961
  6. ↵
    1. Censi, A.,
    2. Marchionni, L., &
    3. Oriolo, G.
    (2008). Simultaneous maximum-likelihood calibration of odometry and sensor parameters. 2008 IEEE International Conference on Robotics and Automation, Pasadena, CA. https://doi.org/10.1109/ROBOT.2008.4543516
  7. ↵
    1. Chen, Y., &
    2. Medioni, G.
    (1992). Object modelling by registration of multiple range images. Image and Vision Computing, 10(3), 145–155. https://doi.org/10.1016/0262-8856(92)90066-C
    CrossRefWeb of Science
  8. ↵
    1. Guehring, J.
    (2001). Reliable 3D surface acquisition, registration and validation using statistical error models. Proc. of the 3rd International Conference on 3D Digital Imaging and Modeling, Quebec City, Canada. https://doi.org/10.1109/IM.2001.924440
  9. ↵
    1. Horn, B. K. P.
    (1987). Closed-form solution of absolute orientation using unit quaternions. Journal of the Optical Society of America A, 4(4), 629–642. https://doi.org/10.1364/JOSAA.4.000629
    CrossRefWeb of Science
  10. ↵
    1. Horn, B. K. P.,
    2. Hilden, H. M., &
    3. Negahdaripour, S.
    (1988). Closed-form solution of absolute orientation using orthonormal matrices. Journal of the Optical Society of America A, 5(7), 1127–1135. https://doi.org/10.1364/JOSAA.4.000629
  11. ↵
    1. Johnson, D. T.,
    2. Nykl, S. L., &
    3. Raquet, J. F.
    (2017). Combining stereo vision and inertial navigation for automated aerial refueling. Journal of Guidance, Control, and Dynamics, 40(9), 2250–2259. https://doi.org/10.2514/1.G002648
  12. ↵
    1. Kolhatkar, C., &
    2. Wagle, K.
    (2021). Review of SLAM algorithms for indoor mobile robot with lidar and RGB-D camera technology. In M. N. Favorskaya, S. Mekhilef, R. K. Pandey, & N. Singh (Eds.), Innovations in electrical and electronic engineering (pp. 397–409). https://doi.org/10.1007/978-981-15-4692-1_30
  13. ↵
    1. Landry, D.,
    2. Pomerleau, F., &
    3. Giguere, P.
    (2019). CELLO-3D: Estimating the covariance of ICP in the real world. 2019 International Conference on Robotics and Automation (ICRA), Montreal, Canada. https://doi.org/10.1109/icra.2019.8793516
  14. ↵
    1. Low, K. -L.
    (2004). Linear least-squares optimization for point-to-plane ICP surface registration (Technical Report No. TR04-004). https://www.comp.nus.edu.sg/~lowkl/publications/lowk_point-to-plane_icp_techrep.pdf
  15. ↵
    1. Markley, F. L., &
    2. Mortari, D.
    (2000). Quaternion attitude estimation using vector observations. The Journal of the Astronautical Sciences, 48(2), 359–380. https://doi.org/10.1007/bf03546284
  16. ↵
    1. Mendes, E.,
    2. Koch, P., &
    3. Lacroix, S.
    (2016). ICP-based pose-graph SLAM. 2016 IEEE International Symposium on Safety, Security, and Rescue Robotics (SSRR), Lausanne, Switzerland. https://doi.org/10.1109/ssrr.2016.7784298
  17. ↵
    1. Pomerleau, F.,
    2. Colas, F., &
    3. Siegwart, R.
    (2015). A review of point cloud registration algorithms for mobile robotics. Now Foundations and Trends. https://doi.org/10.1561/9781680830255
  18. ↵
    1. Prakhya, S. M.,
    2. Bingbing, L.,
    3. Rui, Y., &
    4. Lin, W.
    (2015). A closed-form estimate of 3D ICP covariance. 2015 14th IAPR International Conference on Machine Vision Applications (MVA), Tokyo, Japan. https://doi.org/10.1109/mva.2015.7153246
  19. ↵
    1. Segal, A.,
    2. Haehnel, D., &
    3. Thrun, S.
    (2009). Generalized-ICP. http://www.roboticsproceedings.org/rss05/p21.pdf
  20. ↵
    1. Sorenson, H. W.
    (1966). Kalman filtering techniques. Advances in Control Systems, 3, 219–292. Elsevier. https://www.sciencedirect.com/science/article/abs/pii/B9781483167169500102
    CrossRef
PreviousNext
Back to top

In this issue

NAVIGATION: Journal of the Institute of Navigation: 70 (2)
NAVIGATION: Journal of the Institute of Navigation
Vol. 70, Issue 2
Summer 2023
  • Table of Contents
  • Index by author
Print
Download PDF
Article Alerts
Sign In to Email Alerts with your Email Address
Email Article

Thank you for your interest in spreading the word on NAVIGATION: Journal of the Institute of Navigation.

NOTE: We only request your email address so that the person you are recommending the page to knows that you wanted them to see it, and that it is not junk mail. We do not capture any email address.

Enter multiple addresses on separate lines or separate them with commas.
Accurate Covariance Estimation for Pose Data From Iterative Closest Point Algorithm
(Your Name) has sent you a message from NAVIGATION: Journal of the Institute of Navigation
(Your Name) thought you would like to see the NAVIGATION: Journal of the Institute of Navigation web site.
Citation Tools
Accurate Covariance Estimation for Pose Data From Iterative Closest Point Algorithm
Rick H. Yuan, Clark N. Taylor,, Scott L. Nykl
NAVIGATION: Journal of the Institute of Navigation Jun 2023, 70 (2) navi.562; DOI: 10.33012/navi.562

Citation Manager Formats

  • BibTeX
  • Bookends
  • EasyBib
  • EndNote (tagged)
  • EndNote 8 (xml)
  • Medlars
  • Mendeley
  • Papers
  • RefWorks Tagged
  • Ref Manager
  • RIS
  • Zotero
Share
Accurate Covariance Estimation for Pose Data From Iterative Closest Point Algorithm
Rick H. Yuan, Clark N. Taylor,, Scott L. Nykl
NAVIGATION: Journal of the Institute of Navigation Jun 2023, 70 (2) navi.562; DOI: 10.33012/navi.562
Reddit logo Twitter logo Facebook logo Mendeley logo
  • Tweet Widget
  • Facebook Like
  • Google Plus One
Bookmark this article

Jump to section

  • Article
    • Abstract
    • 1 INTRODUCTION
    • 2 METHODOLOGY
    • 3 RESULTS
    • 4 CONCLUSION
    • HOW TO CITE THIS ARTICLE
    • Footnotes
    • REFERENCES
  • Figures & Data
  • Supplemental
  • References
  • Info & Metrics
  • PDF

Related Articles

  • Google Scholar

Cited By...

  • No citing articles found.
  • Google Scholar

More in this TOC Section

  • Performance of GNSS-SDR for IRNSS L5 Signals Using a Low-Cost RF Front-End
  • Low-Cost, Triple-Frequency, Multi-GNSS PPP and MEMS IMU Integration for Continuous Navigation in Simulated Urban Environments
  • Probabilistic Map Matching for Robust Inertial Navigation Aiding
Show more Original Article

Similar Articles

Keywords

  • covariance estimation
  • ICP
  • iterative closest point
  • uncertainty estimation

Unless otherwise noted, NAVIGATION content is licensed under a Creative Commons CC BY 4.0 License.

© 2023 The Institute of Navigation, Inc.

Powered by HighWire