Research on design, modeling, and maneuverability analysis of hybrid-driven robotic fish
Hybrid-driven robotic fish combines the maneuverability of propeller propulsion with the efficiency of biomimetic fin propulsion, offering potential advantages in underwater exploration and robotic applications. This paper presents the design and development of a hybrid-driven robotic fish that inte...
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| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Frontiers Media S.A.
2025-08-01
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| Series: | Frontiers in Marine Science |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/articles/10.3389/fmars.2025.1648335/full |
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| Summary: | Hybrid-driven robotic fish combines the maneuverability of propeller propulsion with the efficiency of biomimetic fin propulsion, offering potential advantages in underwater exploration and robotic applications. This paper presents the design and development of a hybrid-driven robotic fish that integrates both biomimetic fin and propeller propulsion systems. Initially, the kinematic and dynamic modeling challenges associated with robotic fish are addressed, establishing a comprehensive coupled mathematical model that accounts for the robotic fish’s six degrees of freedom and the actuator dynamics. Subsequently, computational fluid dynamics techniques are employed to simulate a virtual tank for the robotic fish, and hydrodynamic data fitting is performed to determine key parameters such as damping coefficients and thrust coefficients. Finally, a simulation platform based on MATLAB/Simulink is constructed to simulate the robot’s motion, validated through comparisons with simulated calculations and experimental observations. Based on these findings, this paper further analyzes the robotic fish’s maneuverability metrics, including its surge speed, turning radius, and motion characteristics in three-dimensional space, and examines how perturbations in hydrodynamic coefficients affect swimming speed. This study provides valuable insights into the complex motion modeling and performance prediction of hybrid-driven robotic fish, and establishes a foundation for future studies on the motion control of robotic fish. |
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| ISSN: | 2296-7745 |