Efficient AUV Path Planning in Time-Variant Underwater Environment Using Differential Evolution Algorithm

• Published in: Journal of marine science and application Vol. 17; no. 4; pp. 585 - 591
• Main Authors: MahmoudZadeh, S., Powers, D. M. W, Yazdani, A. M., Sammut, K., Atyabi, A.
• Format: Journal Article
• Language: English
• Published: Harbin Harbin Engineering University 01-12-2018; Springer Nature B.V; School of Computer Science, Engineering and Mathematics, Flinders University Tonsley, Adelaide, SA 5042, Australia%Centre for Maritime Engineering, Control and Imaging, Flinders University, Adelaide, SA 5042, Australia%Seattle Children's Research Institute, University of Washington, Washington, WA 98195, USA
• Subjects: Algorithms; Autonomous underwater vehicles; Coastal zone; Collision avoidance; Collision dynamics; Computer simulation; Deployment; Electrical Machines and Networks; Engineering; Evolutionary algorithms; Fields (mathematics); Geotechnical Engineering & Applied Earth Sciences; Initial conditions; Machinery and Machine Elements; Offshore Engineering; Path planning; Planning; Power Electronics; Product design; Research Article; Travel time; Underwater; Differential evolution; Autonomous underwater vehicles; Path planning; Evolutionary algorithms; Obstacle avoidance
• DOI: 10.1007/s11804-018-0034-4
• EISSN: 1993-5048
• ISSN: 1671-9433

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.