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

A heuristic algorithm and path planning technology, applied in the direction of height or depth control, can solve problems such as difficult tracking, high energy consumption for tracking, and rough paths

Active Publication Date: 2019-05-21
UNIV OF ELECTRONIC SCI & TECH OF CHINA
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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 sol

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

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Embodiment 1

[0074]A preferred embodiment of the present invention provides an AUV path planning method based on a population super-heuristic algorithm in an ocean current environment, such as figure 1 shown, including the following steps:

[0075] Step 1: Initialize the population, and then obtain the initial comprehensive cost value of all individuals in the entire population according to the cost function that integrates time efficiency, environmental map, AUV body motion radius of curvature and ocean current information constraints;

[0076] Step 1.1: Set the starting point and ending point of the AUV path, connect the starting point and the ending point, and generate M equal points on the connection line, draw a vertical line according to the connecting line between the starting point and the end point on each equal point point, and obtain M vertical lines, and each vertical line generates i max random points, so that i max group of random points, the i-th group of random points is ...

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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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Application Information

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IPC IPC(8): G05D1/06
Inventor 魏敦文彭倍王斐然吕文薪马虹蛟
Owner UNIV OF ELECTRONIC SCI & TECH OF CHINA
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