AdpInEKF

AdpInEKF for 3D point cloud localization, in which the points of a 3D point cloud set are directly used for measurements to update the predicted state, and any registration algorithms can be employed for the data association process. The states are estimated via Invariant EKF, which as a stable nonlinear observer has particularly suited for state estimation in Lie Group

For more information, please refer to

@article{BarrauB15An,
author = {Axel Barrau and Silvere Bonnabel},
title = {An {EKF-SLAM} algorithm with consistency properties},
journal = {CoRR},
volume = {abs/1510.06263},
year = {2015},
url = {http://arxiv.org/abs/1510.06263},
eprinttype = {arXiv},
eprint = {1510.06263},
timestamp = {Mon, 13 Aug 2018 16:47:54 +0200},
biburl = {https://dblp.org/rec/journals/corr/BarrauB15.bib},
bibsource = {dblp computer science bibliography, https://dblp.org}}

@ARTICLE{Barrau2017The,
author={Barrau, Axel and Bonnabel, Silvère},
journal={IEEE Transactions on Automatic Control},
title={The Invariant Extended Kalman Filter as a Stable Observer},
year={2017},
volume={62},
number={4},
pages={1797-1812},
doi={10.1109/TAC.2016.2594085}}

@article{Barrau2018,
author = {Barrau, Axel and Bonnabel, Silvère},
year = {2018},
month = {05},
pages = {},
title = {Invariant Kalman Filtering},
volume = {1},
journal = {Annual Review of Control, Robotics, and Autonomous Systems},
doi = {10.1146/annurev-control-060117-105010}}

@article{Hartley2020Contact,
author = {Ross Hartley and Maani Ghaffari and Ryan M Eustice and Jessy W Grizzle},
title ={Contact-aided invariant extended Kalman filtering for robot state estimation},
journal = {The International Journal of Robotics Research},
volume = {39},
number = {4},
pages = {402-430},
year = {2020},
doi = {10.1177/0278364919894385},
URL = { https://doi.org/10.1177/0278364919894385},
eprint = { https://doi.org/10.1177/0278364919894385},}

and

@ARTICLE{Tao2022An,
author={Tao, Zhongxing and Xue, Jianru and Wang, Di and Li, Gengxin and Fang, Jianwu},
journal={IEEE Transactions on Intelligent Transportation Systems},
title={An Adaptive Invariant EKF for Map-Aided Localization Using 3D Point Cloud},
year={2022},
volume={},
number={},
pages={1-14},
doi={10.1109/TITS.2022.3200938}}