A UV Path Planning Method Based on Improved Brainstorming Optimization Algorithm

Abstract

The present invention relates to an AUV path planning method based on an improved brainstorming optimization algorithm, which specifically includes the following steps: 1. Construct a three-dimensional optimal navigation surface, randomly generate n groups of initial path control parameters and divide them into m categories, and a group of parameters depends on For an individual, calculate the cost function value of the individual, and the optimal individual of each class becomes the center of the class; 2. Select the individual to be mutated according to the brainstorming optimization algorithm, apply the global optimal strategy to the mutated individual, and obtain a new Individuals, survival of the fittest to update the population; 3. Multiple iterations until the number of iterations meets the termination condition, and output the optimal individual. The invention makes full use of the advantages of the brainstorm optimization algorithm based on global optimization and differential mutation in dealing with low-dimensional problems, captures the characteristics of the cost function well through differential mutation, fully utilizes ocean currents to reduce voyage time, and combines following the global optimal strategy , so that the algorithm has a higher potential to find a better solution in a shorter time.

Description

technical field [0001] The invention relates to the field of AUV path planning and intelligent optimization algorithms, in particular to an AUV path planning method based on an improved brainstorm optimization algorithm. Background technique [0002] The contemporary naval warfare mode is shifting towards intelligence and informationization in order to pursue smaller operational risks and higher combat efficiency, and the importance of underwater unmanned combat systems has become increasingly prominent. AUV is an important part of the underwater unmanned combat system. Path planning is an important technology for AUV to complete combat tasks safely and effectively. It needs to consider constraints such as ocean currents, obstacle avoidance, enemy detection, enemy attack, and its own performance, and pursue energy consumption. , sailing time, safety concealment and other indicators are the best. [0003] The currently commonly used path planning methods mainly include searc...

AI Technical Summary

Problems solved by technology

After the population is initialized, new individuals are generated through operations such as clustering, replacement, selection, and mutation, but there are problems in the selection operation that only some individuals update to follow the global optimum and the step size in the mutation operation cannot be self-adaptive

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