Liu, W;
Liu, Y;
Song, R;
Bucknall, R;
(2015)
Towards the development of an autonomous navigation system for unmanned vessels.
In:
Proceedings of RIN International Navigation Conference 2015.
The Royal Institute of Navigation: Manchester, UK.
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Abstract
This paper discusses the implementation of an intelligent navigation system for an autonomous unmanned surface vessel (USV). The focus is developing a multiple sensor data acquisition and fusion system to provide accurate and continuous information on positions, speeds and courses of the USV itself and also dynamic obstacles known as target ships (TSs). For USV’s autonomous navigation, a Global Positioning System (GPS) receiver, low-cost sensors for dead reckoning (DR) and various types of electronic compasses are employed; For TS’s localisation, the Automatic Identification System (AIS) information has been simulated to estimate and predict the positions of TSs over time. Simulations and practical trials are provided to demonstrate the effectiveness of the proposed system.
| Type: | Proceedings paper |
|---|---|
| Title: | Towards the development of an autonomous navigation system for unmanned vessels |
| Event: | International Navigation Conference |
| Location: | Machester, UK |
| Dates: | 24 February 2015 - 26 February 2015 |
| Open access status: | An open access version is available from UCL Discovery |
| 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, Kalman Filter, Fuzzy Logic |
| UCL classification: | UCL 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 UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences |
| URI: | https://discovery.ucl.ac.uk/id/eprint/1573500 |
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