Abstract
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 language | English (US) |
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Article number | 7139587 |
Pages (from-to) | 2848-2853 |
Number of pages | 6 |
Journal | Proceedings - IEEE International Conference on Robotics and Automation |
Volume | 2015-June |
Issue number | June |
DOIs | |
State | Published - Jun 29 2015 |
Externally published | Yes |
Event | 2015 IEEE International Conference on Robotics and Automation, ICRA 2015 - Seattle, United States Duration: May 26 2015 → May 30 2015 |
ASJC Scopus subject areas
- Software
- Control and Systems Engineering
- Artificial Intelligence
- Electrical and Electronic Engineering