Skip to main content
SpringerLink
Log in

Performance analysis of an INS/SLAM integrated system with respect to the geometrical arrangement of multiple vision sensors

  • Regular Paper
  • Control Applications
  • Published:
International Journal of Control, Automation and Systems Aims and scope Submit manuscript

Abstract

A single vision system is the simplest vision-based method of simultaneous localization and mapping (SLAM) but it cannot reduce navigation errors that occur in the direction of the optical axis of vision sensors. Moreover, the limited observation area of vision sensors sometimes leads to failure in tracking a feature point. A vision sensor-based inertial navigation system INS/SLAM integrated system performs better with multiple vision sensors than with a single vision sensor because the observation area is wider and the impact of the sensitivity of the vision sensors is considerably smaller. However, the geometrical arrangement of multiple vision sensors induces navigation errors. This paper analyzes how the performance of the vision sensor-based INS/SLAM integrated system varies in relation to the geometrical arrangement of multiple vision sensors and the observation area of the vision sensors. The analysis shows that vertical navigation errors decline when the vision sensors are aimed horizontally, and that horizontal navigation errors decline in a similar manner when the vision sensor is aimed vertically; moreover, this behavior is especially evident when the level of sensitivity peaks in the horizontal direction.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  1. M. Bryson and S. Sukkarieh, “Building a robust implementation of bearing-only inertial SLAM for a UAV,” Journal of Field Robotics, vol. 24, no. 1, pp. 113–143, 2007.

    Article  Google Scholar 

  2. H. Durrant-Whyte and T. Bailey, “Simultaneous Localization and mapping: part I/II,” Robotics & Automation Magazine, vol. 13, no. 2, pp. 99–102, no. 3, pp. 108–117, 2006.

    Article  Google Scholar 

  3. J. Kim and S. Sukkarieh, “Autonomous airborne navigation in unknown terrain environments,” IEEE Trans. on Aerospace and Electronic Systems, vol. 40, no. 3, pp. 1031–1045, 2004.

    Article  Google Scholar 

  4. E. Manegatti, Omnidirectional Vision for Mobile Robots, Ph.D. Thesis, The University of Padua, 2002.

  5. L. Zhang, B. Li, and Y. Jia “A practical calibration method for multiple cameras,” Proc. of the 4th International Conference on Image and Graphics, pp. 40–50, 2005.

  6. X. Wang and H. Zhang, “Good image feature for bearing-only SLAM,” Proc. of IEEE/RS International Conference on Intelligent Robots and Systems, pp. 2576–2581, 2006.

  7. R. Munguia and A. Grau, “Delayed initialization for inverse depth monocular SLAM,” Proc. of the 3rd European Conference on Mobile Robots, ECMR 2007, 2007.

  8. D. H. Won, “Improving DR performance using vision based SLAM,” 2007 GNSS Workshop, Nov. 2007.

  9. J. Klippenstein, “Feature initialization for bearingonly visual SLAM Using triangulation and the unscented transform,” Proc. of the IEEE International Conference on Mechatronics and Automation, pp. 1599–1604, Aug. 2007.

  10. J. Kim, Autonomous Navigation for Airborne Application, Ph.D. Thesis, The University of Sydney, May 2004.

  11. D. H. Titterton, Strapdown Inertial Navigation Technology, Peter Peregrinus Ltd., 1997.

  12. S. G. Park, H. C. Jeong, J. W. Kim, D.-H. Hwang, and S. J. Lee, “Magnetic compass fault detection Method for GPS/INS/magnetic compass integrated navigation systems,” International Journal of Control, Automation, and Systems, vol. 9, no. 2, pp. 276–284, 2011.

    Article  Google Scholar 

  13. J. Seo, H. K. Lee, J. G. Lee, and C. G. Park, “Lever arm compensation for GPS/INS/odometer integrated system,” International Journal of Control, Automation, and Systems, vol. 4, no. 2, pp. 247–254, 2006.

    Google Scholar 

  14. D. H. Won, S. Chun, S. Sung, Y. J. Lee, J. Cho, J. Joo, and J. Park, “INS/vSLAM system using distributed particle filter,” International Journal of Control, Automation, and Systems, vol. 8, no. 6, pp. 1232–1240, 2010.

    Article  Google Scholar 

  15. A. Doucet, Sequential Monte Carlo Methods in Practice, Springer, 2001.

  16. B. Ristic, Beyond the Kalman Filter, Artech House, 2004.

  17. R. G. Brown, Introduction to Random Signals and Applied Kalman Filtering, 3rd ed., John Wiley & Sons, 1997.

  18. S. Chun, Performance Improvement of INS/GPS Using Multiple Vision Sensor, Ph.D. Thesis, Konkuk University, 2008.

Download references

Author information

Authors and Affiliations

  1. Korea Aerospace Research Institute, 115 Gwahangno, Yuseong-gu, Daejeon, 305-333, Korea

    Sebum Chun & Moon-Beom Heo

  2. Konkuk University, 1 Hwayangdong, Gwangjin-gu, Seoul, 143-701, Korea

    Dae Hee Won & Young Jae Lee

Authors
  1. Sebum Chun
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Dae Hee Won
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Moon-Beom Heo
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Young Jae Lee
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Young Jae Lee.

Additional information

Recommended by Editorial Board member Kang-Hyun Jo under the direction of Editor Myotaeg Lim.

This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education, Science and Technology (No. 2009-0090722).

Sebum Chun received his Ph.D. degree in Aerospace Engineering from Konkuk University in 2008. He is a senior researcher in the Satellite Navigation team, CNS/ATM and Satellite Navigation Research Center in Korea Aerospace Research Institute (KARI). His research interests include GPS, INS, SLAM and non-linear system state estimation.

Dae Hee Won received his B.S. and M.S. degrees in Aerospace Information Engineering from Konkuk University, Korea, in 2006 and 2008, respectively. He is a Ph.D. candidate in the Department of Aerospace Information Engineering at Konkuk University. His research interests include GPS/INS/Vision system integration, GPS RTK, and nonlinear estimation

Moon-Beom Heo received his M.S. and Ph.D. degrees in Mechanical and Aerospace Information Engineering from Illinois Institute of Technology, U.S. in 1997 and 2004, respectively. He is the head of the Satellite Navigation team, CNS/ATM and Satellite Navigation Research Center in Korea Aerospace Research Institute (KARI). His research interests include GNSS-based navigation system including Ground Based Augmentation System (GBAS).

Young Jae Lee is a Professor in the Department of Aerospace Information Engineering at Konkuk University, Korea. He received his Ph.D. degree in Aerospace Engineering from the University of Texas at Austin in 1990. His research interests include integrity monitoring of GNSS signal, GBAS, RTK, attitude determination, orbit determination, and GNSS-related engineering problems.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Chun, S., Won, D.H., Heo, MB. et al. Performance analysis of an INS/SLAM integrated system with respect to the geometrical arrangement of multiple vision sensors. Int. J. Control Autom. Syst. 10, 288–297 (2012). https://doi.org/10.1007/s12555-012-0209-8

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12555-012-0209-8

Keywords

Search

Navigation