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Unmanned plane cluster cooperation patrol tracking locus programming method based on upper limit confidence interval algorithm

A technology of confidence interval and trajectory planning, which is applied in three-dimensional position/channel control and other directions, and can solve the problem of reducing the intelligence level of UAV group coordination

Active Publication Date: 2017-07-18
BEIHANG UNIV
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Problems solved by technology

This circumvents the fully respectable constraints of decision-making, but reduces the intelligence of drone swarm coordination, making it difficult for drones to effectively search for a target after it has lost track of it

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  • Unmanned plane cluster cooperation patrol tracking locus programming method based on upper limit confidence interval algorithm
  • Unmanned plane cluster cooperation patrol tracking locus programming method based on upper limit confidence interval algorithm
  • Unmanned plane cluster cooperation patrol tracking locus programming method based on upper limit confidence interval algorithm

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[0046] In order to make the purpose, technical solution and advantages of the present invention clearer, the present invention will be further described in detail below in conjunction with the accompanying drawings and specific embodiments.

[0047] According to the UCT algorithm-based UAV swarm cooperative patrol tracking trajectory planning method of the present invention, first input the basic information such as the UAV patrol area, the number of UAVs, and the location of the gas station to initialize, and then according to the current target probability model and teammate model , using a UCT-based reinforcement learning algorithm to determine the direction of UAV movement. Each UAV detects targets within its field of view, and updates the target probability model based on the detection results. Afterwards, the UAV uses the Bayesian probability-based teammate learning method to update the teammate model according to the teammate's running direction. Each aircraft in the f...

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Abstract

The invention relates to an unmanned plane cluster cooperation patrol tracking locus programming method based on an upper limit confidence interval algorithm; the method comprises the following steps: inputting a patrol area, an unmanned plane number and a gas station position; building a target probability model; using the upper limit confidence interval algorithm to solve the next motion direction of the unmanned planes, i.e., randomly selecting a motion direction, using a team mate model to predict a team mate motion direction, obtaining present step bonus and updating the target probability model; selecting the most worthy trying next direction for continuous simulation when the simulation step reaches the maximum simulation duration, continuously simulating until reaching the maximum simulation time, and selecting the direction with the highest average bonus as the unmanned plane real motion direction; allowing the unmanned plane to update the team mate model according to the team mate real motion direction and the maximum probability direction after each decision. The method can adjust according to the unmanned plane hardware performances, is good in robustness, can automatically refuel, patrol and track, and can be widely applied to the unmanned plane automation area patrol and tracking fields.

Description

technical field [0001] The invention relates to UAV trajectory planning technology, in particular to a UAV swarm cooperative patrol tracking trajectory planning method based on an upper-limit confidence interval algorithm. Background technique [0002] With the development of drone technology, the application scenarios and uses of drones are becoming more and more extensive. Due to the characteristics of high freedom of movement, certain load capacity, and relatively stable flight of UAVs, and the battery life of oil-powered UAVs has been greatly improved compared with electric UAVs, UAVs have begun to be used for large-scale patrols Monitoring, especially in places where manual inspection is inconvenient, such as large industrial factories and large farms. These places may be dangerous to people, or manual inspection is prone to blind spots, or the scope is too wide to make manual inspection time-consuming and laborious. In such cases, the advantages of automatic patrol o...

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Application Information

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IPC IPC(8): G05D1/10
Inventor 王田秦若溪陶飞
Owner BEIHANG UNIV
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