Multi-State Tightly-Coupled EKF-Based Radar-Inertial Odometry With Persistent Landmarks

Authors:
Jan Michalczyk, Roland Jung, Christian Brommer, and Stephan Weiss
Publisher:
2023 IEEE International Conference on Robotics and Automation (ICRA)
Year:

This paper presents a Radar-Inertial Odometry (RIO) method that leverages advanced techniques from vision research to accurately estimate a robot’s position and velocity using radar data. The approach combines past robot poses, radar measurements, and Inertial Measurement Unit (IMU) readings in an Extended Kalman Filter (EKF) framework. This method is particularly valuable for Unmanned Aerial Vehicles (UAVs) operating in challenging environments without GNSS, and demonstrates its effectiveness in real flight experiments.

Citation

Citation key:
Michalczyk2023

BibTeX

@inproceedings{Michalczyk2023,
  title = {Multi-State Tightly-Coupled EKF-Based Radar-Inertial Odometry With Persistent Landmarks},
  url = {http://dx.doi.org/10.1109/ICRA48891.2023.10160482},
  DOI = {10.1109/icra48891.2023.10160482},
  booktitle = {2023 IEEE International Conference on Robotics and Automation (ICRA)},
  publisher = {IEEE},
  author = {Michalczyk, Jan and Jung, Roland and Brommer, Christian and Weiss, Stephan},
  year = {2023},
  month = May,
  pages = {4011–4017}
}