Invariant EKF Design for Scan Matching-Aided Localization

@article{Barczyk2015InvariantED,
  title={Invariant EKF Design for Scan Matching-Aided Localization},
  author={Martin Barczyk and Silv{\'e}re Bonnabel and Jean-Emmanuel Deschaud and François Goulette},
  journal={IEEE Transactions on Control Systems Technology},
  year={2015},
  volume={23},
  pages={2440-2448}
}
Localization in indoor environments is a technique that estimates the robot's pose by fusing data from onboard motion sensors with readings of the environment, in our case obtained by scan matching point clouds captured by a low-cost Kinect depth camera. We develop both an invariant extended Kalman filter (IEKF)-based and a multiplicative extended Kalman filter-based solution to this problem. The two designs are successfully validated in experiments and demonstrate the advantage of the IEKF… 

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