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Unmanned aerial vehicle cluster collaborative target searching method imitating biological group negotiation behavior

A target search and drone technology, applied in the field of autonomous control of drones, can solve problems such as low real-time performance and poor adaptability, and achieve the effects of improving control capabilities, good coordination, and improving search efficiency

Pending Publication Date: 2021-10-15
BEIHANG UNIV
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Problems solved by technology

Although this method can obtain the global optimal solution to a certain extent, such methods have shortcomings such as poor adaptability and low real-time performance.

Method used

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  • Unmanned aerial vehicle cluster collaborative target searching method imitating biological group negotiation behavior
  • Unmanned aerial vehicle cluster collaborative target searching method imitating biological group negotiation behavior

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Embodiment Construction

[0093] The effectiveness of the method proposed by the present invention is verified below through a specific instance of UAV cluster co-location. The experimental computer configuration is Intel Core i7-7700HQ processor, 2.8Ghz main frequency, 8G memory, and the software is MATLAB 2018a version. The specific implementation process of the UAV swarm cooperative target search method imitating the biological group negotiation behavior is as follows: Figure 4 shown. Considering the existence of obstacles in the task scene, the inflection point coordinates of the four boundaries of obstacles are: boundary 1-(50,15),(50,21),(75,21),(75,65), (81,65),(81,15); Boundary 2-(15,15), (21,15), (21,65),(15,65); Boundary 3-(35,65), (55 ,65), (55,59), (35,59), boundary 4-(35,45), (55,45), (55,39), (35,39).

[0094] Step 1: Analysis of Ant Colony Foraging Behavior Characteristics and Optimizing Mechanism

[0095] As one of the key points in the simulation of ant colony foraging behavior, t...

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Abstract

The invention discloses an unmanned aerial vehicle cluster collaborative target searching method imitating a biological group negotiation behavior, and belongs to the field of unmanned aerial vehicle autonomous control. The method comprises the following steps: 1, establishing an ant colony foraging behavior characteristic analysis and optimization mechanism; 2, modeling an ant colony negotiation behavior mechanism; 3, mapping an ant colony negotiation mechanism and an unmanned aerial vehicle collaborative target search scene; 4, designing a model of the collaborative search action of the unmanned aerial vehicle; 5, constructing an unmanned aerial vehicle revenue function and a cluster search performance function; and 6, solving an unmanned aerial vehicle cluster collaborative search action. According to the method, the self-organizing control capability of the unmanned aerial vehicle cluster is effectively improved; and while the income of a single unmanned aerial vehicle is ensured, the income maximization of the whole unmanned aerial vehicle cluster in the search process is ensured as much as possible, and the search efficiency is improved.

Description

technical field [0001] The invention relates to an unmanned aerial vehicle cluster cooperative target search method that imitates the negotiation behavior of biological groups, and belongs to the field of autonomous control of unmanned aerial vehicles. Background technique [0002] With the continuous improvement of the autonomy and intelligence level of UAVs, its control methods have gradually changed from a single remote control and program control to human-machine collaborative interactive control, and even completely autonomous control. At the same time, its mission airspace has developed from a safe airspace for intelligence, surveillance and reconnaissance missions to a confrontational airspace such as interference and strike. Considering that the task load of a single UAV is relatively single and the ability to perform tasks is limited, it is necessary to complement the capabilities and coordinate actions of multiple UAVs to improve the combat effectiveness of the ent...

Claims

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Application Information

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IPC IPC(8): G05D1/12
CPCG05D1/12Y02T10/40
Inventor 段海滨申燕凯宋泽昊魏晨邓亦敏
Owner BEIHANG UNIV
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