Skip to main content

Low-Cost Attitude Estimation for a Ground Vehicle

  • Conference paper
  • First Online:
Robot 2015: Second Iberian Robotics Conference

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 417))

  • 3787 Accesses

Abstract

This paper deals with accurate attitude estimation in unmanned ground vehicles using low-cost inertial measurement units. Using Euler angles representation, direct estimations are firstly performed from a single sensor, accelerometer or gyroscope. Then, the low frequency components of the first one and the high frequency components of the second one are fused through an explicit complementary filter (ECF), which uses the quaternion representation. A feedback control structure implements the ECF whose controller parameters determine the filter cut-off frequencies. Finally, a scheduling of controllers in the ECF structure overcomes the shortcomings of accelerometer direct estimation at low frequencies. It provides reliable attitude, although the vehicle movement is accelerated. Illustrative experiments are driven with a Traxxas Car equipped with an Ardupilot Mega 2.5 board.

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

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 169.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 219.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Gebre-Egziabher, D., Hayward, R.C., Powell, J.D.: Design of multi-sensor attitude determination systems. IEEE Transactions on Aerospace and Electronic Systems 40(2), 627–649 (2004)

    Article  Google Scholar 

  2. Barshan, B., Durrant-Whyte, H.F.: Inertial navigation systems for mobile robots. IEEE Transactions on Robotics and Automation 11(3), 328–342 (1995)

    Article  Google Scholar 

  3. De Marina, H.G., Pereda, F.J., Giron-Sierra, J.M., Espinosa, F.: Uav attitude estimation using unscented kalman filter and triad. IEEE Transactions on Industrial Electronics 59(11), 4465–4474 (2012)

    Article  Google Scholar 

  4. Hurak, Z., Rezac, M.: Image-based pointing and tracking for inertially stabilized airborne camera platform. IEEE Transactions on Control Systems Technology 20(5), 1146–1159 (2012)

    Article  Google Scholar 

  5. Fang, L., Antsaklis, P.J., Montestruque, L.A., McMickell, M.B., Lemmon, M., Sun, Y., Fang, H., Koutroulis, I., Haenggi, M., Xie, M., Xie, X.: Design of a wireless assisted pedestrian dead reckoning system - the navmote experience. IEEE Transactions on Instrumentation and Measurement 54(6), 2342–2358 (2005)

    Article  Google Scholar 

  6. Crassidis, J.L., Markley, F.L., Cheng, Y.: Survey of nonlinear attitude estimation methods. Journal of Guidance, Control, and Dynamics 30(1), 12–28 (2007)

    Article  Google Scholar 

  7. Choukroun, D., Bar-Itzhack, I.Y., Oshman, Y.: Novel quaternion kalman filter. IEEE Transactions on Aerospace and Electronic Systems 42(1), 174–190 (2006)

    Article  Google Scholar 

  8. Li, W., Wang, J.: Effective adaptive kalman filter for mems-imu/magnetometers integrated attitude and heading reference systems. Journal of Navigation 66(1), 99–113 (2013)

    Article  Google Scholar 

  9. Mahony, R., Hamel, T., Pflimlin, J.: Nonlinear complementary filters on the special orthogonal group. IEEE Transactions on Automatic Control 53(5), 1203–1218 (2008)

    Article  MathSciNet  Google Scholar 

  10. Euston, M., Coote, P., Mahony, R., Kim, J., Hamel, T.: A complementary filter for attitude estimation of a fixed-wing UAV. In: 2008 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS, pp. 340–345 (2008)

    Google Scholar 

  11. Madgwick, S.O.H., Harrison, A.J.L., Vaidyanathan, R.: Estimation of IMU and MARG orientation using a gradient descent algorithm. In: IEEE International Conference on Rehabilitation Robotics (2011)

    Google Scholar 

  12. Kuipers, J.: Quaternions and Rotation Sequences: A Primer with Applications to Orbits, Aerospace, and Virtual Reality. ser. Princeton paperbacks, Princeton University Press (2002)

    Google Scholar 

  13. Yoo, T.S., Hong, S.K., Yoon, H.M., Park, S.: Gain-scheduled complementary filter design for a mems based attitude and heading reference system. Sensors 11(4), 3816–3830 (2011)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Javier Rico-Azagra .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2016 Springer International Publishing Switzerland

About this paper

Cite this paper

Rico-Azagra, J., Gil-Martínez, M., Rico-Azagra, R., Maisterra, P. (2016). Low-Cost Attitude Estimation for a Ground Vehicle. In: Reis, L., Moreira, A., Lima, P., Montano, L., Muñoz-Martinez, V. (eds) Robot 2015: Second Iberian Robotics Conference. Advances in Intelligent Systems and Computing, vol 417. Springer, Cham. https://doi.org/10.1007/978-3-319-27146-0_10

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-27146-0_10

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-27145-3

  • Online ISBN: 978-3-319-27146-0

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics