Nonlinear path planning method based on hybrid pigeon population algorithm

A technology of trajectory planning and swarm algorithm, applied in the directions of calculation, calculation model, navigation calculation tool, etc., can solve the problems of slow trajectory planning and local optimality of UAVs

Inactive Publication Date: 2017-07-25
SICHUAN UNIV
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AI Technical Summary

Problems solved by technology

[0006] The purpose of the present invention is to solve the problem that the unmanned aerial vehicle track planning speed is slow and easy to fall into local optimum, and a nonlinear track planning method based on mixed pigeon group algorithm is proposed

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  • Nonlinear path planning method based on hybrid pigeon population algorithm
  • Nonlinear path planning method based on hybrid pigeon population algorithm
  • Nonlinear path planning method based on hybrid pigeon population algorithm

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Embodiment Construction

[0030] Below in conjunction with specific embodiment the present invention is described in further detail:

[0031] 1) Express the two-dimensional planning space of UAV flight environment planning as a geometric space area , and determine the starting coordinate point of the flight start (startx, starty), the target point target (targetx, targety);

[0032] 2) Model the threat in the flight mission: convert the threat index such as the geographic location, influence range, and threat level into the matrix information of the discrete planning space. This mainly refers to the radar threat, using a A matrix with four rows and four columns to store threat information, where Represents the number of threats, the first column represents the abscissa of the threat, the second column represents the ordinate of the threat, the third column represents the radius of the threat, and the fourth column represents the level of the threat;

[0033] 3) Initialize various parameters of the...

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Abstract

The invention discloses a nonlinear path planning method based on a hybrid pigeon population algorithm and belongs to the technical field of a single unmanned aerial vehicle. The method comprises determining a flight range and obstacles, initializing various parameters, producing a population initial state value through a random interval method, updating a population position and rate through an ego and social learning factor formula which has an inertia matrix and produces cosine transformation along with the inertia matrix according to the ideology of combination of particle swarm optimization algorithm self-learning and social learning in a map and a compass operator, after cycling upper limit, feeding the data into a landmark operator, sorting the pigeon populations according to adaptability values, recording a center position, calculating the iterative population quantity through a damping matrix producing cosine transformation, updating a position and a rate, and outputting the optimal path. The method improves the accuracy of the algorithm, can produce the optimal solution or the second-best solution very close to the optimal solution and can improve stability of the algorithm and the rate of the path planning.

Description

technical field [0001] The invention relates to a nonlinear track planning method based on a mixed pigeon group algorithm, and belongs to the technical field of unmanned aerial vehicle track planning. Background technique [0002] UAV (Unmanned Aerial Vehicle, UAV) is a weapon and equipment researched by people at home and abroad. It has functions such as automatic take-off and landing, automatic driving, and automatic navigation. Therefore, it has a wide range of applications in military, commercial, aerospace and other fields. Among them, track planning is one of the cores in UAV mission planning system. The purpose of trajectory planning is to select an optimal or very close to optimal suboptimal path from the starting point to the mission location under limited conditions (avoiding threats and no-fly zones, saving fuel, and the shortest path, etc.). At present, there are many trajectory planning methods, which can be roughly divided into two categories: [0003] 1. De...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01C21/20G06N3/00
CPCG01C21/20G06N3/006
Inventor 李智陶国娇李健华伟
Owner SICHUAN UNIV
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