Un-manned plane fairway layout method based on Voronoi graph and ant colony optimization algorithm

An ant colony optimization algorithm and route planning technology, applied in calculation, calculation model, instrument, etc., to achieve good real-time and fast results

Inactive Publication Date: 2008-02-13
BEIHANG UNIV
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Problems solved by technology

[0010] The present invention is a UAV route planning method based on Voronoi diagram and ant colony optimization algorithm, which proposes an improved ant colony optimization algorithm mode

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  • Un-manned plane fairway layout method based on Voronoi graph and ant colony optimization algorithm
  • Un-manned plane fairway layout method based on Voronoi graph and ant colony optimization algorithm
  • Un-manned plane fairway layout method based on Voronoi graph and ant colony optimization algorithm

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Embodiment Construction

[0081] In order to verify the feasibility of the improved ant colony optimization algorithm for route planning in the Voronoi diagram, an adaptive route planning method for intelligent UAVs based on satisfactory decision-making ant colonies in the present invention is carried out using the UAV threat environment shown in Figure 2 The specific implementation steps of the experiment are as follows:

[0082] Step 1: Construct a Voronoi diagram according to the distribution of threat sources, and calculate the total cost of each edge in the Voronoi diagram; parameter initialization: num=30, α=2, β=5, ρ=0.1, Q=100, k=0.6 . Each edge of the Voronoi diagram is assigned an initial pheromone value;

[0083] Step 2: Place all ants on the Voronoi graph node closest to the starting point, and select the next node according to formula (9) until all ants complete the search process:

[0084] P k ( a ...

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Abstract

The invention provides an unmanned aircraft route planning method based on combination of Voronoi diagram and ant group optimizing algorithm. Firstly a model is established in accordance with properties of various threaten sources, e. g. landform, radar, missile and anticraft gun, and the unmanned aircraft route cost includes threaten costs and fuel oil costs; then initial pheromone values are given to each edge of the Voronoi diagram, enabling an ant to begin the search from the Voronoi node nearest to the start point. The marching Voronoi edge is selected based ob the status shift rule, then the search at the Voronoi node nearest to the target point is finished; And when all the ants have finished their own candidate route selection, the pheromones at each edge of the Voronoi diagram are updated in accordance with the improving and updating rules, wherein the pheromones at edges with no ant passing by are evaporated, and the process is repeated until an optimal unmanned aircraft route is found out. The method is characterized by good real-time and high-speed performance, and the found route is closer to the actual optimal unmanned aircraft route.

Description

(1) Technical field [0001] Unmanned Aerial Vehicle (UAV) is a powered, controllable, unmanned tactical aircraft that can carry multiple mission equipment, perform multiple combat missions, and be reusable. Due to its zero casualty risk and high mobility and other advantages, it has attracted great attention from the military of various countries. Path Planning, as a key component of the UAV mission planning system, aims to calculate and select the optimal or suboptimal flight route within an appropriate time, so as to rationally allocate UAV combat resources and achieve The maximum combat effectiveness of the UAV plays a vital role. At present, the research on route planning technology at home and abroad is further developing in the direction of intelligence, real-time, and realizability, but it is basically still in the initial research stage. Ant Colony Optimization (Ant Colony Optimization) algorithm is a newly developed bionic optimization algorithm that simulates the fo...

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Application Information

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IPC IPC(8): G06N3/00G06Q10/00
CPCG05D1/0005
Inventor 段海滨陈宗基刘森琪魏晨
Owner BEIHANG UNIV
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