Approved for public release; distribution is unlimited / Unmanned vehicle technology has matured significantly over the last two decades. This is evidenced by its widespread use in industrial and military applications ranging from deep-ocean exploration to anti-submarine warefare. Indeed, the feasiblity of short-range, special-purpose vehicles (whether aunonomous or remotely operated) is no longer in question. The research efforts have now begun to shift their focus on development of reliable, longer-range, high-endurance and fully autonomous systems. One of the major underlying technologies required to realize this goal is Artificial Intelligence (AI). The latter offers great potential to endow vehicles with the intelligence needed for full autonomy and extended range capability; this involves the increased application of AI technologies to support mission planning and execution, navigation and contingency planning. This thesis addresses two issues associated with the above goal for Autonomous Underwater Vehicles (AUV's). Firstly, a new approach is proposed for path planning in underwater environments that is capable of dealing with uncharted obstacles and which requires significantly less planning time and computer memory. Secondly, it explores the use of expert system technology in the planning of AUV missions.
| Identifer | oai:union.ndltd.org:nps.edu/oai:calhoun.nps.edu:10945/23457 |
| Date | 06 1900 |
| Creators | Ong, Seow Meng |
| Contributors | Kwak, Se-Hung, McGhee, Robert B. |
| Publisher | Monterey, California. Naval Postgraduate School |
| Source Sets | Naval Postgraduate School |
| Language | en_US |
| Detected Language | English |
| Type | Thesis |
| Rights | This publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. As such, it is in the public domain, and under the provisions of Title 17, United States Code, Section 105, it may not be copyrighted. |
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