UCL Discovery
UCL home » Library Services » Electronic resources » UCL Discovery

The Design of an Embedded Multi-Sensor Data Fusion System for Unmanned Surface Vehicle Navigation Based on Real Time Operating System

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 Green open access

[img]
Preview
Text
Liu_The design of an embedded multi-sensor data fusion system for unmanned surface vehicle navigation based on real time operating system_AAM.pdf - Accepted version

Download (1MB) | Preview

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 > Provost and Vice Provost Offices
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.ucl.ac.uk/id/eprint/10056102
Downloads since deposit
43Downloads
Download activity - last month
Download activity - last 12 months
Downloads by country - last 12 months

Archive Staff Only

View Item View Item