Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

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
View PDF0 Cites 83 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

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 model, and successfully applies this improved ant colony optimization algorithm in combination with the Voronoi diagram Solving the problem of UAV route planning in complex dynamic environment

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • 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

Examples

Experimental program
Comparison scheme
Effect test

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 ...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

PUM

No PUM Login to View More

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...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

Application Information

Patent Timeline
no application Login to View More
IPC IPC(8): G06N3/00G06Q10/00
CPCG05D1/0005
Inventor 段海滨陈宗基刘森琪魏晨
Owner BEIHANG UNIV
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic, Popular Technical Reports.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com