Genetic Algorithm Based Path Planning for Seawater Depth Data Measurement in Real Scenarios

Abstract

In this paper, firstly, the movement direction of the measuring ship is clarified, and according to the requirements of factors such as the range of overlap rate is controlled at 10% to 20% and the sea area is completely covered, the optimization equation system is derived, and the objective function is derived through the requirements, and the optimal solution can be derived from the two associations as the 34 measuring lines and the total length of 68 nautical miles of the shortest measuring lines. Using genetic algorithm to examine the real scene of seawater depth data measurement path planning, the length of the measurement line and coverage as an assessment index of the algorithm's subsequent optimization of the object of choice. Through the simulation of genetic mutation, crossover and selection operations, the total length of the shortest survey line is 21.5261 nautical miles, the percentage of missed sea area is 1.6%, and the overlap rate is 13.12% after the iterative solution of the genetic algorithm.