Unmanned aerial vehicle scheduling method and system based on particle swarm optimization and readable storage medium

A technology of particle swarm algorithm and scheduling method, which is applied in the direction of control/regulation system, vehicle position/route/height control, non-electric variable control, etc., and can solve problems such as failure and lost tasks

Inactive Publication Date: 2020-08-25
深圳市易链信息技术有限公司
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Problems solved by technology

On the other hand, UAVs are subject to energy supply, and may be affected by changing environments and various types of obstacles during flight. If there is n

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  • Unmanned aerial vehicle scheduling method and system based on particle swarm optimization and readable storage medium
  • Unmanned aerial vehicle scheduling method and system based on particle swarm optimization and readable storage medium
  • Unmanned aerial vehicle scheduling method and system based on particle swarm optimization and readable storage medium

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[0072] In order to understand the above-mentioned purpose, features and advantages of the present invention more clearly, the present invention will be further described in detail below in conjunction with the accompanying drawings and specific embodiments. It should be noted that, in the case of no conflict, the embodiments of the present application and the features in the embodiments can be combined with each other.

[0073] In the following description, many specific details are set forth in order to fully understand the present invention. However, the present invention can also be implemented in other ways different from those described here. Therefore, the protection scope of the present invention is not limited by the specific details disclosed below. EXAMPLE LIMITATIONS.

[0074] figure 1 It shows a flowchart of a UAV scheduling method based on particle swarm algorithm optimization in the present invention.

[0075] Such as figure 1 As shown, the first aspect of the...

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Abstract

The invention discloses an unmanned aerial vehicle scheduling method and system based on particle swarm optimization and a readable storage medium. The method comprises the following steps: a controlcenter sends a task preparation instruction to a standby unmanned aerial vehicle group; after a task preparation instruction is received, the unmanned aerial vehicle group initializes vehicle body parameters and sends a response data packet to the control center server; the control center performs comprehensive analysis after receiving the response data packet, and determines an unmanned aerial vehicle group executing the task; a conventional path is preliminarily planned for each to-be-flied unmanned aerial vehicle, and a task is executed after receiving a starting instruction;d the unmannedaerial vehicle group and the control center keep a communication state all the time, and the control center performs whole-process scheduling based on particle swarm optimization according to the real-time state of each unmanned aerial vehicle. According to the method disclosed in the invention, by use of the particle swarm optimization technology, unmanned aerial vehicle scheduling intelligence is realized, scheduling management efficiency of the unmanned aerial vehicle group is improved, and the flight energy consumption of the unmanned aerial vehicle during task execution is effectively reduced.

Description

technical field [0001] The present invention relates to the technical field of UAV scheduling, and more specifically, to a UAV scheduling method, system and readable storage medium based on particle swarm algorithm optimization. Background technique [0002] The history of research and development of drones can be traced back to the 1920s. At first, drones were mostly used for military training and actual combat; after nearly a hundred years of research and development, drones have entered the homes of ordinary people, not only for military, It has aroused strong repercussions in the civilian market, and has great development prospects in the commercial field. With the continuous expansion of the use of drones, the environmental factors they face during flight are becoming more and more complex, and the types of tasks they perform are also diverse; model. On the other hand, UAVs are subject to energy supply, and may be affected by changing environments and various types of...

Claims

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Application Information

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IPC IPC(8): G05D1/10
CPCG05D1/104
Inventor 赵亚军陈梁
Owner 深圳市易链信息技术有限公司
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