AUV path planning method in ocean current environment based on population super-heuristic algorithm

Abstract

The invention, which belongs to the field of underwater robots, discloses an unmanned aerial vehicle path planning method in an ocean current environment based on a population super-heuristic algorithm. A population is initialized and initial comprehensive cost values of all individuals in the whole population are obtained according to the cost function; a population basic operation set and a corresponding operation selection probability vector are set; one individual in the population and a population basic operation corresponding to the maximum probability in the operation selection probability vector are selected, the individual is operated, the basic operation of the population is repeated until the entire population is traversed, so that the iteration is completed; the operation selection probability vector is adjusted again and next iteration is carried out until the iteration number reaches a set value; and after iteration completion, an individual with the lowest cost value isselected, one group of control points is formed by combining a starting point, an end point and a fixed control point of a B-spline curve, and an optimal path is generated. Therefore, problems that the path planned based on the existing AUV path planning method is not smooth and is tracked difficultly, and the tracking energy consumption is high are solved.

Description

technical field [0001] The invention belongs to the field of underwater robots and relates to an AUV path planning method in an ocean current environment based on a population super-heuristic algorithm. Background technique [0002] AUV, Autonomous Underwater Vehicle, also known as autonomous underwater robot, has the advantages of large range of activities, good mobility, safety, and intelligence, and is an important tool for completing various underwater tasks. The traditional method of path planning for mobile robots mainly relies on representing the environment as a discretized grid map, and uses search algorithms such as D and A* to search for the absolute shortest path from the start point to the end point. There are two problems in this search-based path planning method. On the one hand, when the scale of the map increases, especially when it is extended to three-dimensional space, the efficiency of the search algorithm will drop sharply; on the other hand, this metho...

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Problems solved by technology

[0009] The object of the present invention is to provide a AUV path planning method based on population super-heuristic algorithm in the ocean current environment, which solves the problem that the path planned by the existing AUV path planning method is not smooth, it is difficult to track and the problem of high energy consumption for tracking

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