A Distributed Multi-UAV Task Allocation Method in Uncertain Environment

A multi-UAV and task allocation technology, applied in the direction of instruments, three-dimensional position/channel control, control/regulation system, etc., can solve the problem of large amount of calculation, and achieve the effect of high success rate and high task income

Active Publication Date: 2021-12-28
NORTHWESTERN POLYTECHNICAL UNIV
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Problems solved by technology

However, the amount of calculation required by the existing methods is too large, how to improve the calculation efficiency of the algorithm without reducing the execution efficiency of the robust task allocation algorithm is a technical problem to be solved by those skilled in the art

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  • A Distributed Multi-UAV Task Allocation Method in Uncertain Environment
  • A Distributed Multi-UAV Task Allocation Method in Uncertain Environment
  • A Distributed Multi-UAV Task Allocation Method in Uncertain Environment

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Embodiment Construction

[0066] The present invention will be further described below in conjunction with the accompanying drawings and embodiments, and the present invention includes but not limited to the following embodiments.

[0067] Such as figure 1 Shown, the steps of the present invention are as follows:

[0068] Step 1: Cooperative assignment model for multi-UAV time-sensitive tasks under uncertain parameters

[0069] UAV formation by N a It consists of two drones, all of which are of the same type. There are N in the task execution area t targets, the UAV formation needs to perform time-sensitive tasks for each target, and the execution time of each time-sensitive task is t j (j=1,2...,N t ), and its time window constraints are as follows:

[0070] ET j ≤t j ≤LT j (1-1)

[0071] Among them, ET j is the earliest allowable execution time of task j, LT j is the latest allowable start execution time of task j. The execution of a time-sensitive task must satisfy the time window cons...

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Abstract

The invention provides a distributed multi-UAV task assignment method in an uncertain environment. Firstly, a collaborative task assignment model is established, and each UAV performs its own task bundle update and construction, and then the UAV formation conducts consensus negotiation , to achieve the goal of maximizing the overall revenue under uncertain parameters. The present invention utilizes the consistency bundle algorithm CBBA to solve the time-sensitive task collaborative allocation problem of multiple UAVs when the task environment has uncertain parameters under the distributed architecture, and uses the Gaussian process regression model to capture the impact of uncertain parameters on task allocation benefits Influence to participate in the assignment process to ensure the actual execution effect of task assignment results, and use active learning and manifold learning methods to improve the computational efficiency of the algorithm.

Description

technical field [0001] The invention relates to a multi-unmanned aerial vehicle task allocation method. Background technique [0002] At present, with the improvement of drone technology, multiple drones can form a cluster formation through coordination and cooperation to complete tasks that cannot or are difficult to complete with a single drone. Therefore, research on multi-UAV systems has received extensive attention. Multi-UAV task allocation is one of the key technologies for multi-UAV collaborative mission planning. Its goal is to optimize the overall performance of the mission based on the prior intelligence information of the mission area and target and under the premise of considering specific constraints. Or sub-optimal as the goal, and reasonably assign specific operational tasks to members of the UAV formation. With the continuous improvement of the performance of UAVs and the increase of interference factors in the mission environment, some prior data often ha...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G05D1/10
CPCG05D1/104
Inventor 符小卫王辉潘静高晓光
Owner NORTHWESTERN POLYTECHNICAL UNIV
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