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Autonomous task assignment method for UAV swarms based on biological predation energy model

A technology of biological predation and distribution methods, applied in the direction of non-electric variable control, instruments, control/regulation systems, etc.

Active Publication Date: 2020-12-15
BEIHANG UNIV
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  • Claims
  • Application Information

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Problems solved by technology

[0005] The present invention is an autonomous task assignment method for UAV clusters based on a biological predation energy model, and its purpose is to provide a distributed task assignment model that supports task load balance and ensures robustness of task performance in an unknown dynamic environment. Solve key technical issues such as the dependence of traditional centralized planning methods on central nodes and the consistency of traditional distributed planning methods

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  • Autonomous task assignment method for UAV swarms based on biological predation energy model
  • Autonomous task assignment method for UAV swarms based on biological predation energy model
  • Autonomous task assignment method for UAV swarms based on biological predation energy model

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Embodiment Construction

[0073] The effectiveness of the collaborative task assignment method proposed in the present invention will be verified through specific examples below. In this example, given N u = 5 unmanned aerial vehicles participate in the target search and strike missions to the 1km × 1km unknown area. The starting positions of the 5 drones are respectively set to S 1 =[0,100,50] T , S 2 =[0,300,50] T , S 3 =[0,500,50] T , S 4 =[0,700,60] T , S 5 =[0,900,60] T ; The reconnaissance end position is respectively set to E 1 =[1000,100,50] T ,E 2 =[1000,300,50] T ,E3 =[1000,500,50] T ,E 4 =[1000,700,60] T ,E 5 =[1000,900,60] T , the unit is m. The UAV motion model adopts the following second-order linear system:

[0074]

[0075] Among them, v u is the flight speed of the UAV, unit m / s; θ u is the current heading of the UAV, in rad; [u v , u θ , u h ] T is the control vector of the UAV, which controls the forward acceleration, heading angular velocity and vertical...

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Abstract

The invention discloses an unmanned aerial vehicle cluster autonomous task allocation method based on a biological predation energy model. The method comprises the following implementation steps of 1,initializing cooperative task allocation; step 2, leading-following global information interaction; 3, performing striking task pre-distribution based on a biological predation total energy relationship; 4, cooperative strike task allocation based on the biological predation energy balance model; 5, attack task conflict resolution based on opportunistic hunting negotiation; and step 6, outputtingand executing a cooperative task allocation result. According to the method, a distributed task allocation model supporting task load balance and guaranteeing task efficiency robustness is provided,and resource consumption type tasks such as long-term, persistent search and strike executed in an unknown dynamic environment of an unmanned aerial vehicle cluster can be effectively supported.

Description

technical field [0001] The present invention is an autonomous task assignment method of UAV cluster based on biological predation energy model, which is used to solve the task planning problem of UAV cluster search and strike multi-target in unknown dynamic environment, and belongs to the field of multi-unmanned system decision-making and control . Background technique [0002] Under the current trend of UAV design pursuing miniaturization, light load, and concealment, the possibility of achieving complex tasks through a single UAV is gradually decreasing. In contrast, UAV clusters use complementary performance advantages to cooperate to complete tasks, which can not only maintain low-cost development, but also improve the execution robustness of the system under the overall multi-task state, and have good applications in both military and civilian fields. prospect. However, how to allocate the subtasks of each UAV in the swarm under the drive of a specific task, so that i...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G05D1/10
CPCG05D1/104
Inventor 段海滨张岱峰邓亦敏魏晨
Owner BEIHANG UNIV