Research On Underwater Glider Path Planning Based On Improved Particle Swarm Optimization

Underwater glider is an emerging underwater robot in recent years,with no power to promote the characteristics of temperature can be converted into mechanical energy.Rely on their own energy to adjust the attitude and pitch angle,the use of underwater temperature difference between surface and bottom can achieve underwater glide.To overcome the traditional underwater robot energy consumption restrictions,with a greater range,longer time for the ability to detect under the sea;at the same time because no power to promote the noise is minimal,strong concealment,with high practical value.Path planning is one of the important research topics of underwater robots.Path planning problem is how to achieve the optimal path according to an optimization goal in the determined environment.It is necessary to understand the working principle of the underwater glider.First,from the analysis of the force of the underwater glider,the system composition is analyzed,and the process of converting the temperature difference into mechanical energy is analyzed in detail.The power of the underwater glider comes from the ocean temperature difference energy.According to the temperature-sensitive characteristics of the power system,this paper uses the data of the National Oceanographic Data Center Ocean Climate Laboratory WOA13 10 ° to 20 ° north latitude,110 ° to 120 ° Between January 2013,the temperature data of the sea area in January to achieve the temperature requirements of the sea area to quantify the distinction,to distinguish the specific underwater glider airworthiness or not the topographic map.At the same time,the measured data of 0.25 latitude and longitude are refined,and the topographic maps of the adjacent data points are different from 0.05 latitude and longitude.Accurate environmental data is an important prerequisite for determining the efficiency of path planning.In this paper,the improved particle swarm algorithm is used to plan the path of the underwater glider.In order to solve the problem of the instability of the particles at the initial stage of the particle swarm algorithm,this paper uses the anti-learning method to initialize the particle swarm,select the best half of the fitness Particle as the initial population,to speed up the convergence rate of the algorithm.Because the path navigation is influenced by the two factors of path length and water depth,this paper introduces the calculation of the penalty function to optimize the fitness function.In order to further strengthen the depth search ability of PSO algorithm and avoid the local optimum,this paper combines the differential evolution operation to explore the excellent solution around the current population.Simulation results show that the improved particle swarm optimization algorithm has a faster convergence rate and a better planning route.