Swarm Intelligence (SI) constitutes a rapidly growing area of research. At the same time trajectory planning in a dynamic environment still constitutes a very challenging research problem. This paper presents a new approach to path planning in dynamic environments based on Ant Colony Optimisation (ACO). Assumptions, a concise description of the method developed and results of real navigational situations (case studies with comments) are included. The developed solution can be applied in decision support systems on board a ship or in an intelligent Obstacle Detection and Avoidance system, which constitutes a component of Unmanned Surface Vehicle (USV) Navigation, Guidance and Control systems.


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    Titel :

    Ship's Trajectory Planning for Collision Avoidance at Sea Based on Ant Colony Optimisation


    Beteiligte:

    Erschienen in:

    Erscheinungsdatum :

    2014




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Print


    Sprache :

    Englisch



    Klassifikation :

    BKL:    55.86 Schiffsverkehr, Schifffahrt / 53.84 Ortungstechnik, Radartechnik / 42.89 Zoologie: Sonstiges / 55.54 Flugführung / 42.89 / 53.84 / 55.20 / 55.86 / 55.20 Straßenfahrzeugtechnik / 55.44 Schiffsführung / 55.54 / 55.44
    Lokalklassifikation TIB:    275/5680/7035



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