Journal article
Efficient AUV Path Planning in Time-Variant Underwater Environment Using Differential Evolution Algorithm
Journal of marine science and application, Vol.17(4), pp.585-591
2018
Abstract
Robust and efficient AUV path planning is a key element for persistence AUV maneuvering in variable underwater environments. To develop such a path planning system, in this study, differential evolution (DE) algorithm is employed. The performance of the DE-based planner in generating time-efficient paths to direct the AUV from its initial conditions to the target of interest is investigated within a complexed 3D underwater environment incorporated with turbulent current vector fields, coastal area, islands, and static/dynamic obstacles. The results of simulations indicate the inherent efficiency of the DE-based path planner as it is capable of extracting feasible areas of a real map to determine the allowed spaces for the vehicle deployment while coping undesired current disturbances, exploiting desirable currents, and avoiding collision boundaries in directing the vehicle to its destination. The results are implementable for a realistic scenario and on-board real AUV as the DE planner satisfies all vehicular and environmental constraints while minimizing the travel time/distance, in a computationally efficient manner.
Details
- Title
- Efficient AUV Path Planning in Time-Variant Underwater Environment Using Differential Evolution Algorithm
- Authors/Creators
- S. MahmoudZadeh - Flinders UniversityD. M. W. Powers - Flinders UniversityA. M. Yazdani - Flinders UniversityK. Sammut - Flinders UniversityA. Atyabi - Seattle Children's Hospital
- Publication Details
- Journal of marine science and application, Vol.17(4), pp.585-591
- Publisher
- Harbin Engineering Univ
- Number of pages
- 7
- Identifiers
- 991005592755507891
- Copyright
- © Harbin Engineering University and Springer-Verlag GmbH Germany, part of Springer Nature 2018
- Murdoch Affiliation
- School of Engineering and Energy; Centre for Water, Energy and Waste
- Language
- English
- Resource Type
- Journal article
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