MATEC Web Conf.
Volume 139, 20172017 3rd International Conference on Mechanical, Electronic and Information Technology Engineering (ICMITE 2017)
|Number of page(s)||5|
|Published online||05 December 2017|
Monocular Visual-Inertial State Estimation for Micro Aerial Vehicles
Faculty of Information Technology, Beijing University of Technology
* Corresponding author: e-mail: email@example.com
Autonomous micro aerial vehicles (MAVs) equipped with onboard sensors, are idea platforms for missions in complex and confined environments for its low cost, small size and agile maneuver. Due to the size, power, weight and computation constraints inherent in the filed of MAVs, monocular visual-inertial system that consist of one camera and an inertial measurement (IMU) are the most suitable sensor suit for MAVs. In this paper, we proposed a monocular visual-inertial algorithm for estimating the state of a MAV. Firstly, the Semi-Direct Visual Odometry (SVO) algorithm used as the vision front-end of our framework was modified so that it can be used for forward-looking camera case. Second, an Error-state Kalman Filter was designed so that it can fuse the output of the SVO and IMU data to estimate the full state of the MAVs. We evaluated the proposed method with EuRoc Dataset and compare the results to the state-of-the-art visual-inertial algorithm, VINS-Mono. Experiments show that our estimator can achieve comparable accurate results.
© The Authors, published by EDP Sciences, 2017
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (http://creativecommons.org/licenses/by/4.0/).
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