A Track Planning Method for Unmanned Surface Vehicles Based on Quantum Ant Colony Algorithm

Abstract

The invention discloses a quantum ant colony algorithm-based unmanned surface vehicle navigation path planning method and belongs to the unmanned surface vehicle and navigation path planning technicalfield. According to the method of the invention, a quantum ant colony algorithm is adopted to solve the navigation path planning problem of an unmanned surface vehicle. The method includes the following steps that: the static environment model of a navigation area is established according to an obstacle distribution condition in a geographic information database; the navigation path planning comprehensive evaluation function of the unmanned surface vehicle is established according to the objective function and constraints of the navigation path planning of the unmanned surface vehicle; and the quantum ant colony algorithm is adopted to perform global static navigation path planning on the unmanned surface vehicle. The algorithm provided by the invention not only can reflect the high efficiency of quantum computing, but also maintain the good searching capacity and strong robustness of the ant colony algorithm, and therefore, the calculation speed of the algorithm can be can improved.With the method adopted, the optimal navigation path of the unmanned surface vehicle under a complex sea condition can be obtained effectively and quickly, and therefore, the optimal navigation path can be obtained under a premise that the unmanned surface vehicle satisfies the constraints, and thus, mission requirements can be satisfied.

Description

technical field [0001] The invention belongs to the technical field of unmanned surface craft and track planning, and in particular relates to a track planning method for unmanned surface craft based on a quantum ant colony algorithm. Background technique [0002] With the continuous development of unmanned platforms, unmanned surface vehicles, as an important tool for monitoring the marine environment and performing dangerous tasks instead of manned ships, have broad application prospects. In recent years, unmanned surface vehicles have become a research hotspot in the field of maritime intelligent transportation, and its track planning is one of the key technologies for the intelligence of unmanned surface vehicles. The purpose of track planning for unmanned surface vehicles is to use terrain environment information and mission information to plan the trajectory of unmanned surface vehicles from the starting point to the target point under the premise of satisfying various...

AI Technical Summary

Problems solved by technology

Quantum computing has the characteristics of good parallelism, high exponential storage capacity and exponential acceleration, which can overcome the shortcomings of ant colony algorithm, which is easy to fall into local optimum and slow calculation speed.

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