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Fixed-wing unmanned aerial vehicle cluster collaborative path planning method based on optimal pheromone grey wolf algorithm

A path planning, UAV technology, applied in vehicle position/route/height control, non-electric variable control, instruments, etc., to achieve the effect of enhancing convergence speed, speeding up solution efficiency, and improving optimization ability

Pending Publication Date: 2021-11-09
DALIAN MARITIME UNIVERSITY
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  • Description
  • Claims
  • Application Information

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Problems solved by technology

[0004] According to the above proposal how to solve the collaborative path planning problem of fixed-wing unmanned aerial vehicle swarms in high-dimensional, multi-constraint and complex scenes, a collaborative path planning method for fixed-wing unmanned aerial vehicles swarms based on the optimal pheromone gray wolf algorithm is provided

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  • Fixed-wing unmanned aerial vehicle cluster collaborative path planning method based on optimal pheromone grey wolf algorithm
  • Fixed-wing unmanned aerial vehicle cluster collaborative path planning method based on optimal pheromone grey wolf algorithm
  • Fixed-wing unmanned aerial vehicle cluster collaborative path planning method based on optimal pheromone grey wolf algorithm

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Embodiment

[0139] The simulation experiment is carried out on the Windows 10 operating system, the algorithm running platform is MATLAB2016B, and the planning space size is 75km×75km×15km. For N=5 fixed-wing UAV clusters, the above method is implemented in three scenarios of different complexity, and the implementation steps for each scenario are as follows:

[0140] Step 1: Establish a three-dimensional map containing M=5 threat sources, and determine the starting point and target point of each UAV. The information of the threat source is shown in Table 1, and the starting point and target point of the UAV are shown in Table 2. Divide the line ST between the starting point S and the target point T of each UAV into 11 parts, that is, the track of each UAV contains 10 track points.

[0141] Table 1 Threat source information

[0142]

[0143] Table 2 UAV starting point information

[0144]

[0145]

[0146] Step 2: Establish a cost function for cluster trajectory planning;

[0...

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Abstract

The invention provides a fixed-wing unmanned aerial vehicle cluster collaborative path planning method based on an optimal pheromone grey wolf algorithm. The method comprises the following steps: s1, establishing a three-dimensional map containing M threat sources; s2, establishing a cluster route planning cost function; s3, planning the tracks of all fixed-wing unmanned aerial vehicle clusters by adopting a grey wolf algorithm based on optimal pheromones. According to the method, a cooperative flight path planning problem of a fixed-wing unmanned aerial vehicle cluster in a three-dimensional scene is solved by adopting an optimal pheromone grey wolf algorithm, and a plurality of optimal grey wolves are selected based on a wolf pack grade system in the algorithm to update pheromones on flight path points; wherein, the exploration stage of each gray wolf follows the guidance of pheromones so as to improve the convergence speed and the solution stability of the algorithm, and the rotation angle constraint of the unmanned aerial vehicles and the collision avoidance constraint between the unmanned aerial vehicles are met. According to the technical scheme, the problem of fixed-wing unmanned cluster collaborative path planning in a high-dimensional and multi-constraint complex scene is solved.

Description

technical field [0001] The present invention relates to the technical field of unmanned aerial vehicle cluster collaborative path planning track planning, in particular, to a fixed-wing unmanned aerial vehicle cluster cooperative path planning method based on the preferred pheromone gray wolf algorithm. Background technique [0002] Facing the increasingly complex modern air environment, using UAV clusters to work together can improve work efficiency and mission success rate. At the same time, fixed-wing UAVs are widely used in geological exploration, disaster rescue, military reconnaissance and strikes because of their long battery life, fast flight speed, and large payload. Coordinated trajectory planning is a key technology to ensure the effective work of fixed-wing UAV swarms. In a specific mission scenario, it is necessary to find multiple ways to enable each UAV to reach its respective target point from the starting point according to a better flight route. This fligh...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G05D1/10
CPCG05D1/104
Inventor 刘中常杨川龙岳伟
Owner DALIAN MARITIME UNIVERSITY
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