Marine search and rescue activities have been plagued with the problem of risking the lives of rescuers in
rescue operations. With increasing developments in sensor technologies, it became a necessity in the
marine search and rescue community to develop an autonomous marine craft to assist in rescue
operations. Autonomy of marine craft requires a robust localization technique and process. To apply
robust localization to marine craft, GPS technology was used to determine the position of the marine craft
at any given point in time. Given that the operational environment of the marine was at open air, river, sea
etc. GPS signal was always available to the marine craft as there are no obstructions to GPS signal.
Adequate cognizance of the current position and states of an unmanned marine craft was a critical
requirement for navigation of an unmanned surface vehicle (USV). The unmanned surface vehicle uses
GPS in conjunction with state estimated solution provided by inertial sensors. In the absence of the GPS
signal, navigation is resumed with a digital compass and inertial sensors to such a time when the GPS
signal becomes accessible.
GPS based navigation can be used for an unmanned marine craft with the mathematical modelling of the
craft meeting the functional requirements of an unmanned marine craft. A low cost GPS unit was used in
conjunction with a low cost inertial measurement unit (IMU) with sonar for obstacle detection. The use of
sonar in navigation algorithm of marine craft was aimed at surveillance of the operational environment of
the marine craft to detect obstacles on its path of motion. Inertial sensors were used to determine the
attitude of the marine craft in motion. / Thesis (M.Sc.Eng.)-University of KwaZulu-Natal, Durban, 2011.
| Identifer | oai:union.ndltd.org:netd.ac.za/oai:union.ndltd.org:ukzn/oai:http://researchspace.ukzn.ac.za:10413/5122 |
| Date | January 2011 |
| Creators | Onunka, Chiemela. |
| Contributors | Bright, Glen., Stopforth, Riaan. |
| Source Sets | South African National ETD Portal |
| Language | en_ZA |
| Detected Language | English |
| Type | Thesis |
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