This paper presents a distributed mission planning system that enables a team of autonomous underwater vehicles (AUVs) for effective underwater chlorophyll sampling. The proposed system is developed based on a distributed algorithm that optimizes the real-time task allocation and mission planning of AUVs in a cooperative fashion while considering environmental and vehicular constraints to ensure efficient and coordinated sampling efforts. A realistic case study of a chlorophyll sampling mission in Australia's Great Barrier is utilized to investigate the performance of the proposed system in a restricted mission time and in the exposure to the uncertainty of the mission. Simulation studies confirm the effectiveness and resilience of the proposed system and showcase its potential as a valuable tool for advancing underwater chlorophyll sampling missions.


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    Title :

    AUVs' Distributed Mission Planning System for Effective Underwater Chlorophyll Sampling


    Contributors:


    Publication date :

    2024-02-12


    Size :

    1383782 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English




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