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Unmanned aerial vehicle route planning system and unmanned aerial vehicle route planning method based on genetic programming

A technology of genetic programming and track planning, which is applied in the direction of genetic rules, genetic models, data processing applications, etc., to achieve the effects of rapid optimization process, optimized fitness, and reduced computing time

Inactive Publication Date: 2016-04-20
SHANGHAI JIAO TONG UNIV
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Problems solved by technology

[0006] Aiming at the above-mentioned deficiencies in the prior art, the present invention proposes a UAV track planning system and method based on genetic programming, adopts the genetic programming algorithm as the track planning algorithm, and through the improvement and innovation of the genetic programming algorithm, its Applied to complex multi-objective optimization problems, the tree structure is used to perform initialization, decoding, selective breeding and other steps to continuously optimize the track

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  • Unmanned aerial vehicle route planning system and unmanned aerial vehicle route planning method based on genetic programming
  • Unmanned aerial vehicle route planning system and unmanned aerial vehicle route planning method based on genetic programming
  • Unmanned aerial vehicle route planning system and unmanned aerial vehicle route planning method based on genetic programming

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Embodiment 1

[0040] Such as figure 1 As shown, this embodiment includes the following steps:

[0041] Step A, the UAV task module constructs an optimization equation;

[0042] Step B, the scene information module defines the terrain and threats, such as image 3 shown;

[0043] Step C, the genetic programming algorithm module preprocesses the initial information: use the original threat and map information, use the map information to make a two-dimensional planar map, add the threat location and threat radius marked in step B to the map; and use the UAV The model module calculates the parameters in the fitness value function according to the cost functions such as path length and flight height.

[0044] Step D, initialize the population: define the population size as 100, and set the number of each depth as n=100 / (maximum-1), where: maximum is the set maximum depth. Define the GPLIB_Entity class, that is, the individual class, and the generated individuals are stored in the collection ...

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Abstract

Disclosed are an unmanned aerial vehicle (UAV) route planning system and a UAV route planning method based on genetic programming. The method comprises the following steps: initial populations of a tree structure are built through a UAV model module; each individual is decoded and the fitness value of each individual is calculated through a genetic programming algorithm module; selecting and breeding operations are performed between the populations, and an optimal population is obtained through a plurality of iteration processes; and finally, an optimal individual is selected from the optimal population and decoded through a UAV task module to obtain an optimal route of genetic programming. According to the invention, initializing, decoding, selecting and breeding steps are performed by use of the tree structure to optimize the route constantly. The optimization process is quick, the method is visual, the performance of the planned route is improved, the computing time is reduced, the degree of fitness is optimized, and the system and the method are of very high feasibility and robustness.

Description

technical field [0001] The present invention relates to a technology in the field of path planning and artificial intelligence, in particular to a system and method for UAV track planning based on genetic programming. Background technique [0002] The path planning system is mainly used in the path planning problems of UAVs, robots, surface ships, vehicles, etc. Path planning is to find a path that satisfies specific constraints from the initial state point to the target state point of the moving body according to a certain evaluation standard system. [0003] Track planning is a kind of path planning, which is more difficult and complicated than general path planning. Due to the complex motion performance of the aircraft and the complexity of the mission environment, the trajectory planning system needs to comprehensively consider factors such as the maneuverability of the aircraft, mission time, terrain environment, and enemy-controlled areas. The trajectory planning sys...

Claims

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Application Information

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IPC IPC(8): G06Q10/04G06N3/12
CPCG06Q10/047G06N3/126
Inventor 李建勋杨晓宇
Owner SHANGHAI JIAO TONG UNIV
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