Comparison of an attitude estimator based on the Lagrange-d'Alembert principle with some state-of-the-art filters

Maziar Izadi, Ehsan Samiei, Amit K. Sanyal, Vijay Kumar

Research output: Contribution to journalConference Articlepeer-review

18 Scopus citations


Discrete-time estimation of rigid body attitude and angular velocity without any knowledge of the attitude dynamics model, is treated using the discrete Lagrange-d'Alembert principle. Using body-fixed sensor measurements of direction vectors and angular velocity, a Lagrangian is obtained as the difference between a kinetic energy-like term that is quadratic in the angular velocity estimation error, and an artificial potential obtained from Wahba's function. An additional dissipation term that depends linearly on the angular velocity estimation error is introduced, and the discrete Lagrange-d'Alembert principle is applied to the Lagrangian with this dissipation. An implicit and an explicit first-order version of this discrete-time estimation scheme is presented. A comparison of this estimator is made with certain state-of-the-art attitude estimators in the absence of bias in sensor readings. Numerical simulations show that this estimator is robust and unlike extended Kalman filter-based schemes, its convergence does not depend on the gain values. In addition, the variational estimator is found to be more computationally efficient than these other estimators.

Original languageEnglish (US)
Article number7139587
Pages (from-to)2848-2853
Number of pages6
JournalProceedings - IEEE International Conference on Robotics and Automation
Issue numberJune
StatePublished - Jun 29 2015
Externally publishedYes
Event2015 IEEE International Conference on Robotics and Automation, ICRA 2015 - Seattle, United States
Duration: May 26 2015May 30 2015

ASJC Scopus subject areas

  • Software
  • Control and Systems Engineering
  • Artificial Intelligence
  • Electrical and Electronic Engineering


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