An interval number optimization algorithm for path planning of robotic fish in the uncertain environment with ocean currents

Robotic fish is more and more widely used in the ocean engineering field because of its advantages in invisibility, efficiency, mobility and so on, whose path planning is an important issue to accomplish underwater missions. However, the uncertainty of ocean currents is existed inevitably in practic...

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Veröffentlicht in:Journal of marine science and technology Jg. 30; H. 4; S. 980 - 995
Hauptverfasser: Tian, Qunhong, Li, Jialin, Wang, Tao, Liu, Bing, Li, Hongyu
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Tokyo Springer Japan 09.10.2025
Schlagworte:
Automotive Engineering
Engineering
Engineering Design
Engineering Fluid Dynamics
Mechanical Engineering
Offshore Engineering
Original Article
Path planning
Robust optimization, interval number
Robotic fish
Ocean currents
ISSN:0948-4280, 1437-8213
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Beschreibung
Zusammenfassung:Robotic fish is more and more widely used in the ocean engineering field because of its advantages in invisibility, efficiency, mobility and so on, whose path planning is an important issue to accomplish underwater missions. However, the uncertainty of ocean currents is existed inevitably in practice, which has great influence on path planning design for the robotic fish. The objective functions including path travel time, smoothness and safety factor are given to evaluate the performance for path planning in this paper, and interval number path planning problem is proposed for robotic fish in uncertain ocean environment. Based on the interval number theory, the uncertain path planning issue for robotic fish is transformed into a two-level and two-objective optimization problem, which is solved to obtain the robust optimal path by the genetic algorithm. The proposed interval number optimization algorithm has good decision space; the decisions can be made by the decision-makers flexibly in light of the experimental analysis. The simulation results illustrate the effectiveness and feasibility of the proposed algorithm.
ISSN:0948-4280
1437-8213
DOI:10.1007/s00773-025-01095-7