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 warfare. Indeed, the feasibility of short range, special-purpose vehicles (whether autonomous 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 fully automated and extended range capability; this involves the increased application of AI techniques 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. (KR)


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    Title :

    Mission Planning Expert System with Three-Dimensional Path Optimization for the NPS Model 2 Autonomous Underwater Vehicle


    Contributors:
    S. M. Ong (author)

    Publication date :

    1990


    Size :

    196 pages


    Type of media :

    Report


    Type of material :

    No indication


    Language :

    English




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