Liu, W;
Liu, Y;
Song, R;
Bucknall, R;
(2018)
The Design of an Embedded Multi-Sensor Data Fusion System for Unmanned Surface Vehicle Navigation Based on Real Time Operating System.
In:
Proceedings of the OCEANS’18 MTS/IEEE Kobe / Techno-Ocean 2018.
IEEE
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Abstract
This paper describes the design and implementation of a practical multi sensor data fusion system for unmanned surface vehicle (USV) navigation. The system employs an embedded Linux board as the main on-board control module to extract and preprocess raw measurements from various navigational sensors using the real time operating system (RTOS). An unscented Kalman Filter (UKF) based data fusion algorithm has been developed to fuse the obtained and preprocessed sensor measurements and provide more reliable and accurate estimations of USV’s navigational data in real time. The results demonstrate the effectiveness of the data fusion algorithm in reducing unpredicted errors of a standalone sensor.
| Type: | Proceedings paper |
|---|---|
| Title: | The Design of an Embedded Multi-Sensor Data Fusion System for Unmanned Surface Vehicle Navigation Based on Real Time Operating System |
| Event: | OCEANS’18 MTS/IEEE Kobe / Techno-Ocean, 28-31 May 2018, Kobe, Japan |
| Location: | Kobe Japan |
| Dates: | 28 May 2018 - 31 May 2018 |
| ISBN-13: | ISBN: 978-1-5386-1654-3 |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1109/OCEANSKOBE.2018.8559352 |
| Publisher version: | https://doi.org/10.1109/OCEANSKOBE.2018.8559352 |
| Language: | English |
| Additional information: | This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions. |
| Keywords: | multi-sensor data fusion, real time operating system, unmanned surface vehicle |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Mechanical Engineering |
| URI: | https://discovery-pp.ucl.ac.uk/id/eprint/10056102 |
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