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Robust Localization and Localizability Estimation with a Rotating Laser Scanner

Weikun Zhen, Sam Zeng and Sebastian Scherer
Conference Paper, IEEE International Conference on Robotics and Automation 2017, May, 2017

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Abstract

This paper presents a robust localization approach that fuses measurements from inertial measurement unit (IMU) and a rotating laser scanner. An Error State Kalman Filter (ESKF) is used for sensor fusion and is combined with a Gaussian Particle Filter (GPF) for measurements update. We experimentally demonstrated the robustness of this implementation in various challenging situations such as kidnapped robot situation, laser range reduction and various environment scales and characteristics. Additionally, we propose a new method to evaluate localizability of a given 3D map and show that the computed localizability can precisely predict localization errors, thus helps to find safe routes during flight.

BibTeX Reference
@conference{Zhen-2017-18126,
title = {Robust Localization and Localizability Estimation with a Rotating Laser Scanner},
author = {Weikun Zhen and Sam Zeng and Sebastian Scherer},
booktitle = {IEEE International Conference on Robotics and Automation 2017},
keyword = {Localization, Localizability, MAV, Laser Scanner},
month = {May},
year = {2017},
}
2017-09-13T10:38:07+00:00