JRM Vol.24 No.2 pp. 389-398
doi: 10.20965/jrm.2012.p0389


Attitude Determination by Globally and Asymptotically Stable Estimation of Gyroscope Bias Error with Disturbance Attenuation and Rejection

Hideaki Yamato, Takayuki Furuta, and Ken Tomiyama

Future Robotics Technology Center, Chiba Institute of Technology, 2-17-1 Tsudanuma, Narashino, Chiba 275-0016, Japan

September 21, 2011
February 13, 2012
April 20, 2012
attitude estimation, inertial sensors, quaternion feedback, Wahba’s problem
This paper presents a new methodology of attitude determination for cost-effective and small inertial measurement units, consisting of tri-axial gyroscope sensors, accelerometers, and geo-magnetometers. Introduced for algorithm development is a quaternion feedback structure, where bias terms in the gyroscope rate information, appearing in the feedback loop, are identified with the theoretical guarantee of global and asymptotical stability. The bias-term identification and modification process is performed continuously without the influence of disturbance by combining the proposed disturbance evaluation scheme and conventional vector matching method with an adaptive parameter configuration. Practical validity of the presented framework is fully evaluated by experiments. It is shown that the approach in this paper can offer drift-free performance with disturbance attenuation and rejection under arbitrary attitude test motion of spatial rotation and translation.
Cite this article as:
H. Yamato, T. Furuta, and K. Tomiyama, “Attitude Determination by Globally and Asymptotically Stable Estimation of Gyroscope Bias Error with Disturbance Attenuation and Rejection,” J. Robot. Mechatron., Vol.24 No.2, pp. 389-398, 2012.
Data files:
  1. [1] H. Fourati, N. Manamanni, L. Afilal, and Y. Handrich, “A Rigid Body Attitude Estimation for Bio-Logging Application: A Quaternion-Based Nonlinear Filter Approach,” The 2009 IEEE/RSJ Int. Conf. on Intelligent Robots and Systems, St. Louis, USA, pp. 558-563, 2009.
  2. [2] M. Euston, P. Coote, R. Mahony, J. Kim, and T. Hamel, “A Complementary Filter for Attitude Estimation of a Fixed-Wing UAV,” The 2008 IEEE/RSJ Int. Conf. on Intelligent Robots and Systems, Nice, France, pp. 340-345, 2008.
  3. [3] S. Suzuki, M. Tawara, D. Nakazawa, and K. Nonami, “Research on Attitude Estimation Algorithm under Dynamic Acceleration,” J. of the Robotics Society of Japan, Vol.26, No.6, pp. 626-634, 2008 (in Japanese).
  4. [4] E. Foxlin, “Inertial Head-Tracker Sensor Fusion by a Complementary Separate-Bias Kalman Filter,” IEEE Virtual Reality Annual Int. Symposium, Santa Clara, USA, pp. 185-194, 1996.
  5. [5] P. Setoodeh, A. Khayatian, and E. Frajah, “Attitude Estimation By Separate-Bias Kalman Filter-Based Data Fusion,” The J. of Navigation, Vol.57, No.2, pp. 261-273, 2004.
  6. [6] H. Rehbinder and X. Hu, “Drift-free attitude estimation for accelerated rigid bodies,” Automatica, Vol.40, pp. 653-659, 2004.
  7. [7] Y. S. Suh, S. K. Park, H. J. Kang, and Y. S. Ro, “Attitude Estimation Adaptively Compensating External Acceleration,” JSME Int. J., Series C, Vol.49, No.1, pp. 172-179, 2006.
  8. [8] X. Yun and E. R. Bachmann, “Design, Implementation, and Experimental Results of a Quaternion-Based Kalman-Filter for Human Body Motion Tracking,” IEEE Trans. Robotics, Vol.22, No.6, pp. 1216-1227, 2006.
  9. [9] G. Wahba, “Problem 65-1, A Least Squares Estimation of Satellite Attitude,” SIAM Review, Vol.7, No.3, p. 409, 1965.
  10. [10] P. Davenport, “A Vector Approach to the Algebra of Rotations with Applications,” NASA Technical Note, Goddard Space Flight Center, NASA TN D-4696, 1968.
  11. [11] J. Keat, “Analysis of Least-Square Attitude Determination Routine DOAOP,” NASA Contractor Report (CR), NASA-CR-183450, 1977.
  12. [12] M. D. Shuster and S. D. Oh, “Three-Axis Attitude Determination from Vector Observations,” AIAA J. of Guidance and Control, Vol.4, No.1, pp. 70-77, 1981.
  13. [13] J. K. Thienel and R. M. Sanner, “A Coupled Nonlinear Spacecraft Attitude Controller and Observer with an Unknown Constant Gyro Bias and Gyro Noise,” IEEE Trans. Automatic Control, Vol.48, No.11, pp. 2011-2015, 2003.
  14. [14] J. L. Crassidis, F. L. Markley, and Y. Cheng, “Survey of Nonlinear Attitude Estimation Methods,” AIAA J. of Guidance, Control, and Dynamics, Vol.30, No.1, pp. 12-28, 2007.
  15. [15] M. D. Shuster, “A Survey of Attitude Representations,” AAS The J. of the Astronautical Sciences, Vol.41, No.4, pp. 439-517, 1993.
  16. [16] H. Baruh, “ANALYTICAL DYNAMICS,” pp. 355-390, McGraw-Hill, 1999.
  17. [17] J. S.-C. Yuan, “Closed-Loop Manipulator Control Using Quaternion Feedback,” IEEE J. of Robotics and Automation, Vol.4, No.4, pp. 434-440, 1988.
  18. [18] H. K. Khalil, “Nonlinear Systems, 3rd Ed.,” pp. 111-181, Prentice Hall, 2001.
  19. [19] F. L. Markley, “Attitude Determination Using Vector Observations: A Fast Optimal Matrix Algorithm,” AAS The J. of The Astronautical Sciences, Vol.41, No.2, pp. 261-280, 1993.
  20. [20] F. L.Markley, “Attitude Determination Using Two Vector Measurements,” AIAA 1999 Flight Mechanics Symposium, NASA Goddard Space Flight Center, Greenbelt, USA, pp. 39-52, 1999.
  21. [21] I. Y. Bar-Itzhack, “New Method for Extracting the Quaternion from a Rotation Matrix,” AIAA J. of Guidance, Control, and Dynamics, Vol.23, No.6, pp. 1085-1087, 2000.
  22. [22] F. L. Markley, “Unit Quaternion from Rotation Matrix,” AIAA J. of Guidance, Control, and Dynamics, Vol.31, No.2, pp. 440-442, 2008.
  23. [23] M. D. Shuster, “Maximum Likelihood Estimation of Spacecraft Attitude,” AAS J. of the Astronautical Science, Vol.37, No.1, pp. 79-88, 1989.

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