Immune genetic algorithm for AUV (Autonomous Underwater Vehicle) real-time path planning

Abstract

The invention relates to a real-time path planning method of AUV (Autonomous Underwater Vehicle), in particular to a method for carrying out online, real-time local path planning according to an online map in an AUV real-time collision preventation process. The method comprises the steps of: setting the quantity of small populations according to the quantity of path points of the AUV, initializing; carrying out immune selection on each small population to obtain subgroups; carrying out genetic manipulation on one subgroup, carrying out cell cloning on the other subgroup; then clustering through a vaccination and an antibody to form the next generation of small population, judging whether the next generation of small population meets the conditions or not; if yes, selecting optimal individuals of the small populations; and selecting the optimal individuals from the set consisting of all optimal individuals to be used as a planning path. According to the invention, the diversity of the population is maintained by using an antibody clustering principle, the premature convergence of an algorithm is avoided, and the global optimization is facilitated. The established immune genetic algorithm is used for clustering and analyzing generated filial generations by adopting a self-regulating mechanism, and the diversity of the population is ensured.

Description

technical field [0001] The invention relates to a real-time path planning method for an autonomous underwater vehicle (AUV, Autonomous Underwater Vehicle), more specifically, a method for performing online and real-time local path planning according to an online map during the real-time collision avoidance process of the AUV. Background technique [0002] An autonomous underwater robot is a submersible that carries its own energy, relies on an autonomous navigation system, and through intelligent planning and decision-making, navigates to the operating area autonomously and completes the operating mission autonomously. Autonomy requires autonomous underwater robots to adapt to changing and complex external environments autonomously without external control, especially to deal with unknown obstacles in advance. This requires that the autonomous underwater robot should not only have the real-time collision avoidance function, but also have the ability of online and real-time l...

AI Technical Summary

Problems solved by technology

However, the traditional genetic algorithm has two problems of premature maturity and sl

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