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arXiv · 1503.01407

Invariant EKF Design for Scan Matching-aided Localization

Martin Barczyk·Silvère Bonnabel·Jean-Emmanuel Deschaud·François Goulette
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Abstract

Localization in indoor environments is a technique which 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 (MEKF)-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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BibTeXRIS

Martin Barczyk, Silvère Bonnabel, Jean-Emmanuel Deschaud, François Goulette. 2015-03-04. Invariant EKF Design for Scan Matching-aided Localization. https://arxiv.org/abs/1503.01407

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