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Three-dimensional ant colony flight path optimization method

An optimization method and technology of three-dimensional ant colony, applied in the field of three-dimensional track, can solve the problems of falling into local optimum, long calculation time, slow convergence speed of ant colony algorithm, etc., to improve search efficiency, speed up convergence speed, and reduce the feasibility of search node effect

Pending Publication Date: 2020-11-06
SHANGHAI DIANJI UNIV
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Problems solved by technology

[0003] The basic ant colony algorithm has the disadvantages of slow convergence, long calculation time, and easy to fall into local optimum prematurely. These algorithms have certain limitations in three-dimensional track planning, especially in large-scale three-dimensional space, it is not easy to Plan an optimal trajectory, slow convergence

Method used

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  • Three-dimensional ant colony flight path optimization method
  • Three-dimensional ant colony flight path optimization method
  • Three-dimensional ant colony flight path optimization method

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specific Embodiment

[0055] Such as image 3 Shown is the algorithm flowchart of the embodiment of the method of the present invention, specifically comprises:

[0056] Step 1: Establish a 3D environment model;

[0057] Step 2: Input the initial pheromone, select the starting point and end point, and set the algorithm parameters; among them, the algorithm parameters include the total number of iterations N, the total number of ants per generation M, the pheromone intensity coefficient Q, the pheromone volatilization coefficient ρ, and the initial information heuristic factor α and initial expectation heuristic factor β;

[0058] Step 3: Put the ant at the starting point and calculate the current state transition probability;

[0059] Step 4: Design a search domain around each node, set a priority search set for nodes in the search domain, and calculate the adaptive threshold of nodes in the search domain;

[0060] Step 5: Compare the current state transition probability with the adaptive thresh...

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Abstract

The invention relates to a three-dimensional ant colony flight path optimization method. By adding an angle factor into a local search space, the airspace search range of a flight path is reduced, search feasible nodes in a three-dimensional space are reduced, the convergence rate of an algorithm is increased, and the search efficiency of an unmanned aerial vehicle in the three-dimensional space is improved.

Description

technical field [0001] The invention relates to the technical field of three-dimensional track, in particular to a three-dimensional ant colony track optimization method. Background technique [0002] With the rise of the field of intelligence, the trajectory planning of UAVs has become the focus of research by scholars at home and abroad. Whether it is in the military or civilian fields, the value of UAVs is getting higher and higher. Conventional trajectory planning algorithms include heuristic A* algorithm, artificial potential field method, particle swarm algorithm and genetic algorithm. [0003] The basic ant colony algorithm has the disadvantages of slow convergence, long calculation time, and easy to fall into local optimum prematurely. These algorithms have certain limitations in three-dimensional track planning, especially in large-scale three-dimensional space, it is not easy to An optimal flight path is planned, and the convergence is slow. Compared with other s...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01C21/20G01C21/34
CPCG01C21/20G01C21/3446
Inventor 鲍世通
Owner SHANGHAI DIANJI UNIV