| Title: | OS7-3 Enhancing semi-dense monocular vSLAM used for multi-rotor UAV navigation in indoor environment by fusing IMU data |
|---|---|
| Publication: | ICAROB2018 |
| Volume: | 23 |
| Pages: | 391-394 |
| ISSN: | 2188-7829 |
| DOI: | 10.5954/ICAROB.2018.OS7-3 |
| Author(s): | Andrey Bokovoy, Konstantin Yakovlev |
| Publication Date: | February 2, 2018 |
| Keywords: | vision-based SLAM, IMU, monocular camera, navigation, UAV |
| Abstract: | We propose the enhancement of the modern vision-based monocular simultaneous localization and mapping (vSLAM) method, e.g. LSD-SLAM, used for compact multi-rotor UAV indoor navigation, by fusing inertial measurement unit (IMU) data with camera images. We suggest removing the cost-expensive loop-closure optimization algorithm from the vSLAM pipeline and replacing it with the computationally efficient flow estimation procedure based purely on IMU data. The input IMU flow is being processed by the Extended Kalman Filter (EKF) based techniques for localization purposes and used further in LSD-SLAM algorithm for UAV pose estimation. We evaluate the proposed algorithm using the modeled indoor environment originally used for RoboCup Rescue Simulation League 2013 competition and "hector_quadrotor" – commonly used in modelling simulated UAV model. Evidently, implementation of the suggested enhancement results in significant drop-down of the runtime and leads to obtaining maps and trajectories of higher accuracy. |
| PDF File: | https://alife-robotics.co.jp/members2018/icarob/data/html/data/OS_pdf/OS7/OS7-3.pdf |
| Copyright: | © The authors. This article is distributed under the terms of the Creative Commons Attribution License 4.0, which permits non-commercial use, distribution and reproduction in any medium, provided the original work is properly cited. See for details: https://creativecommons.org/licenses/by-nc/4.0/ |
(c)2008 Copyright The Regents of ALife Robotics Corporation Ltd. All Rights Reserved.