Method for planning paths on basis of ocean current prediction models

Abstract

The invention belongs to the field of underwater robot control, and discloses a method for planning paths on the basis of ocean current prediction models. The method includes steps of carrying out rasterization processing on sailing regions according to path critical points; predicting ocean current for the sailing regions by the aid of regional ocean modes and acquiring real-time ocean current information by means of fitting computation; marking prohibited areas by the aid of electronic ocean map information; storing prohibition information of different depths and starting point and end pointlocation information according to plain grids at different depths, and storing longitudes and latitudes of various points of the grids, whether the points are the prohibited areas or not and whetherend points are reached or not; computing the directions from current locations to the end points and determining optional actions in travel directions at all next steps; seeking the optimal strategiesby the aid of Q-learning and outputting the paths. The optimal strategies are planned in Markov decision-making processes. The method has the advantages that influence of the real-time ocean currenton path planning is sufficiently considered, fitting is carried out by the aid of BP (back propagation) neural networks and bagging algorithms, the optimal solution can be sought by means of reinforcement learning, accordingly, the convergence speeds can be increased, and the computational complexity can be lowered.

Description

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AI Technical Summary

Benefits of technology

The present invention considers real-time ocean currents and predicts future ocean elements to plan paths more effectively. It uses advanced algorithms to obtain real-time ocean current information and finds the optimal solution through reinforcement learning. This speeds up the planning process and improves the accuracy of the planned path.

Problems solved by technology

This patented describes different methods for guiding autonomously operated dronys (AU) boats towards their destination without causing any harm during exploration activities. These techniques involve analyzing sea waves and other environmental variables like wave height, water temperature, pressure, orientation angle, directionality, and acceleration measurements over time to create a virtual world called "undersea". To accurately navigate through the marine environment, there must exist advanced technologies including radomics, image processing, machine vision, and artificial intelligence. Current approaches rely heavily on mathematical models derived from past experience and require significant computational resources.

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