A Trajectory Base Method for Ship's Safe Path Planning | Zendy

Agnieszka Lazarowska | Zendy

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A Trajectory Base Method for Ship's Safe Path Planning

Author(s) -

Agnieszka Lazarowska

Publication year - 2016

Publication title -

procedia computer science

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.334

H-Index - 76

ISSN - 1877-0509

DOI - 10.1016/j.procs.2016.08.118

Subject(s) - computer science , trajectory , heuristic , base (topology) , path (computing) , set (abstract data type) , ant colony optimization algorithms , motion planning , matlab , process (computing) , mathematical optimization , operator (biology) , algorithm , robot , artificial intelligence , mathematics , mathematical analysis , physics , astronomy , biochemistry , chemistry , repressor , transcription factor , gene , programming language , operating system

The paper introduces a new algorithmic approach for ship's safe path planning. A new method utilizes a database containing a set of trajectories. An algorithm searches the trajectory base in order to find a safe trajectory that meets the optimality criterion (criteria) selected by the system operator. The method presented can be applied in a navigation Decision Support System. The method can also be adopted for applications in other environments, where similar problem occurs - in navigation of mobile robots or aircrafts. It should be emphasized that dynamic properties of an own ship are included in the calculations.The paper describes assumptions and constraints taken into account in the solution construction process, a presentation of the Trajectory Base Algorithm (TBA) Decision Support System (DSS) and the explanation of the algorithm operation principle. A successful application of the method proposed is confirmed by simulation tests carried out with the use of MATLAB environment. The results of calculations with the use of implemented algorithm are presented and compared with solutions received by an application of an approach based on a heuristic method - the Ant Colony Optimisation. The outcome and achievements are summarized in the conclusions

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