Awesome
inekf-ros
This repository contains a ROS wrapper for the C++ inekf library located at https://github.com/RossHartley/invariant-ekf
This filter can be used to estimate a robot's 3D pose and velocity using an IMU motion model for propagation. The following measurements are currently supported:
- Prior landmark position measurements (localization)
- Estaimted landmark position measurements (SLAM)
- Kinematic and contact measurements
Installation
TODO
Parameters
TODO
Examples
TODO
Citations
The contact-aided invariant extended Kalman filter is described in:
- R. Hartley, M. G. Jadidi, J. Grizzle, and R. M. Eustice, “Contact-aided invariant extended kalman filtering for legged robot state estimation,” in Proceedings of Robotics: Science and Systems, Pittsburgh, Pennsylvania, June 2018.
@INPROCEEDINGS{Hartley-RSS-18,
AUTHOR = {Ross Hartley AND Maani Ghaffari Jadidi AND Jessy Grizzle AND Ryan M Eustice},
TITLE = {Contact-Aided Invariant Extended Kalman Filtering for Legged Robot State Estimation},
BOOKTITLE = {Proceedings of Robotics: Science and Systems},
YEAR = {2018},
ADDRESS = {Pittsburgh, Pennsylvania},
MONTH = {June},
DOI = {10.15607/RSS.2018.XIV.050}
}
The core theory of invariant extended Kalman filtering is presented in:
- Barrau, Axel, and Silvère Bonnabel. "The invariant extended Kalman filter as a stable observer." IEEE Transactions on Automatic Control 62.4 (2017): 1797-1812.
@article{barrau2017invariant,
title={The invariant extended Kalman filter as a stable observer},
author={Barrau, Axel and Bonnabel, Silv{\`e}re},
journal={IEEE Transactions on Automatic Control},
volume={62},
number={4},
pages={1797--1812},
year={2017},
publisher={IEEE}
}