Overcoming Bias: Equivariant Filter Design for Biased Attitude Estimation with Online Calibration
This letter presents a new generic formulation for a gyroscope aided attitude estimator using N direction measurements. The approach incorporates navigation, extrinsic calibration for all direction sensors, and gyroscope bias states in a single geometric structure. The proposed filter-based estimator improves the transient response, and the asymptotic bias and extrinsic calibration estimation compared to state-of-the-art approaches. The estimator is verified in simulations and tested in real-world experiments.
Citation
@article{Fornasier2022,
title = {Overcoming Bias: Equivariant Filter Design for Biased Attitude Estimation With Online Calibration},
volume = {7},
ISSN = {2377-3774},
url = {http://dx.doi.org/10.1109/LRA.2022.3210867},
DOI = {10.1109/lra.2022.3210867},
number = {4},
journal = {IEEE Robotics and Automation Letters},
publisher = {Institute of Electrical and Electronics Engineers (IEEE)},
author = {Fornasier, Alessandro and Ng, Yonhon and Brommer, Christian and Bohm, Christoph and Mahony, Robert and Weiss, Stephan},
year = {2022},
month = Oct,
pages = {12118–12125}
}