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Invariant EKF Design for Scan Matching-aided Localization

Abstract : 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 design.
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Submitted on : Friday, January 15, 2016 - 12:23:12 PM
Last modification on : Thursday, September 24, 2020 - 5:04:02 PM
Long-term archiving on: : Saturday, April 16, 2016 - 10:32:50 AM

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Martin Barczyk, Silvère Bonnabel, Jean-Emmanuel Deschaud, François Goulette. Invariant EKF Design for Scan Matching-aided Localization. IEEE Transactions on Control Systems Technology, Institute of Electrical and Electronics Engineers, 2015, 23 (6), pp.2440-2448. ⟨10.1109/TCST.2015.2413933⟩. ⟨hal-01256770⟩

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