Research On Configuration Optimization And Obstacle Avoidance Strategy Of Wave Glider

This paper designs a wave glider that converts wave energy into forward kinetic energy.Then it carries photovoltaic solar panels,breeze energy storage devices,and wave power generation devices as auxiliary power sources to provide energy supply for the electromechanical and sensor equipment of the surface hull,achieving low-carbon zero-emission,long-endurance,and wide-range navigation.Facing the complex and changeable marine environment,how to make the wave glider adapt to different sea conditions to achieve high operating efficiency is particularly important,such as shape optimization to reduce resistance,real-time obstacle avoidance for marine obstacles,etc.The underactuated and weak maneuverability of the wave glider make optimizing its form configuration and obstacle avoidance research highly challenging.Firstly,this paper takes the configuration optimization of the wave glider appearance shape as the research object,selects the Shear Stress Transport(SST)model based on the N-S equation,and applies Fluent software to analyze the effects of different pitches between the flapping wing of the underwater glider and different pitch angles on the motion efficiency of the wave glider;In this paper,six groups of underwater gliding with different spaces and different angles are arranged for simulation experiments by setting the calculation domain,boundary conditions,residuals,inlet velocity,and sea conditions,etc.By analyzing the velocity and pressure contours obtained from the simulation,the results show that: with the increase of flapping wing pitch,the interference between the flapping wing becomes smaller and smaller,and the wave glider effectiveness is the highest when the flapping wing pitch is20mm;With the increase of flapping wing pitch angle,the effectiveness of the underwater glider first increases and then decreases,of which 15 ° is the peak.Then,Q-learning of reinforcement learning is used to study the wave glider obstacle avoidance.By setting a reasonable reward mechanism,wave glider executes an optimal obstacle avoidance strategy for obstacles in complex marine environments.Finally,the model is tested for obstacle avoidance by setting up different complex obstacle environments on the MATLAB simulation experiment platform to verify the robustness and effectiveness of the model.The results show that the wave glider can successfully perform obstacle avoidance missions in different complex obstacle environments,proving the model’s feasibility.This paper reveals that the spacing and angle of the underwater glider wings have a correlating effect on the efficiency of the wave glider through the research on the configuration optimization and obstacle avoidance strategy of the wave glider,and the appropriate spacing and angle can improve the operational efficiency to different degrees;Using reinforcement learning to do obstacle avoidance research on wave gliders can better adapt to various marine environments and have strong robustness,and reinforcement learning is more suitable for underactuated and weakly controlled ocean exploration robots like wave gliders.