Trajectory Prediction and Optimized Search Path Planning for Missing Deep-Sea Submersibles under Ocean Current Influence

This paper investigates the trajectory of a deep-sea submersible under the influence of ocean currents after it loses power, and makes a probabilistic assessment based on its possible arrival position, and then plans an optimal search and rescue path. Based on the data of each element of the Aeolian seabed water, this paper relies on the principle of ocean hydrodynamics and calculates the velocity distribution of ocean currents using Euler’s and Bernoulli’s equations. By analyzing the dynamic process of the submersible, a system of coupled second-order differential equations is constructed and solved numerically using the fourth-order Runge-Kutta method. With the initial position and velocity determined, the model can accurately provide the trajectory of the submersible without considering the stochastic currents. A search model is then developed to deploy initial search points and search patterns to minimize the time to locate the missing submersible. The trajectory of the submersible in dynamic motion is simulated by a stochastic wandering model, and then the statistical probabilities of various possible routes and position distributions are computed in the presence of random current noise disturbances. The search weights are assigned according to the probability of the diver’s distribution area, distance and time from the main ship, and particle swarm optimization is used to solve the optimal solution of the parameters to obtain the best search path.