Combined System Identification and State Estimation for a Quadrotor UAV

Authors:
Christoph Böhm, Christian Brommer, Alexander Hardt-Stremayr, and Stephan Weiss
Publisher:
IEEE International Conference on Robotics and Automation (ICRA)
Year:

This paper proposes a probabilistic approach for online system identification and self-calibration in small rotorcraft Unmanned Aerial Vehicles (UAVs) for improved control design and navigation. The approach integrates the system identification and state estimation processes into a single framework, allowing for self-awareness and self-healing, and uses a combination of inertial cues, dynamic modeling, and an additional sensor for convergence to the optimal value. The results are supported by simulations using realistic data in Gazebo.

Citation

Citation key:
Bohm2021

BibTeX

@inproceedings{Bohm2021,
  title = {Combined System Identification and State Estimation for a Quadrotor UAV},
  url = {http://dx.doi.org/10.1109/ICRA48506.2021.9561850},
  DOI = {10.1109/icra48506.2021.9561850},
  booktitle = {2021 IEEE International Conference on Robotics and Automation (ICRA)},
  publisher = {IEEE},
  author = {Bohm, Christoph and Brommer, Christian and Hardt-Stremayr, Alexander and Weiss, Stephan},
  year = {2021},
  month = May,
  pages = {585–591}
}