Experimental trajectory optimization of a flapping fin propulsor using an evolutionary strategy

Area of Science:

• Robotics and Control Systems
• Bio-inspired Engineering
• Fluid Dynamics

Background:

• Autonomous underwater vehicles (AUVs) require efficient propulsion systems.
• Bio-inspired designs, mimicking fish swimming, offer potential for novel AUV propulsion.
• Optimizing flapping fin trajectories is crucial for performance.

Purpose of the Study:

• To experimentally optimize bio-inspired flapping fin trajectories for AUV propulsion.
• To evaluate trajectories for both side-force and rear (thrust) generation.
• To identify optimal parameters for efficiency and force generation.

Main Methods:

• Utilized a spherical parallel manipulator to execute flapping fin trajectories.
• Employed a covariance matrix adaptive evolutionary strategy for optimization.
• Scored trajectories based on force set-point accuracy and propulsive efficiency.

Main Results:

• Identified optimal trajectories for side-force (3D and linear) and thrust generation.
• Demonstrated rapid convergence and accurate force set-point achievement.
• Found side-force generation to be more efficient around Reynolds number 1000.

Conclusions:

• Bio-inspired flapping fins can be effectively optimized for AUV propulsion.
• Linear trajectories show potential for efficient side-force generation.
• Optimization primarily enhances maneuver efficiency after initial force set-point achievement.