Unmanned system cluster control method based on deep reinforcement learning

A technology of reinforcement learning and cluster control, applied in two-dimensional position/channel control, vehicle position/route/altitude control, control/regulation system and other directions, which can solve problems such as poor environmental adaptability of unmanned system cluster control methods

Active Publication Date: 2020-12-11
HARBIN INST OF TECH
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Problems solved by technology

[0004] In order to solve the problem of poor environmental adaptability of the existing unmanned system cluster control method, the present invention

Method used

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  • Unmanned system cluster control method based on deep reinforcement learning
  • Unmanned system cluster control method based on deep reinforcement learning
  • Unmanned system cluster control method based on deep reinforcement learning

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specific Embodiment 1

[0056] according to figure 1 As shown, the present invention provides a method for controlling unmanned system clusters based on deep reinforcement learning, specifically:

[0057] A method for unmanned system swarm control based on deep reinforcement learning, comprising the following steps:

[0058] Step 1: Form an unmanned system cluster by N unmanned systems, according to figure 1 As shown, the information of the surrounding environment is detected by the sensors of each unmanned system, and the information of the surrounding environment includes target information, obstacle information and surrounding unmanned system information; its communication range and perception range are as follows image 3 shown.

[0059] The step 1 is specifically:

[0060] The information of the surrounding environment is detected by the communication equipment and perception sensors of each unmanned system, and the target information, obstacle information and surrounding unmanned system info...

specific Embodiment 2

[0095] The experiment of the present invention adopts the digital model of the rotor UAV to carry out simulation verification.

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Abstract

The invention relates to an unmanned system cluster control method based on deep reinforcement learning. The invention relates to the technical field of unmanned system cluster control, and aims at solving a problem that an existing unmanned system cluster control method is poor in environmental adaptability. The method comprises the steps of in an unmanned system cluster, using each unmanned system to detect environment information; dividing the environment information into target information, obstacle information and other unmanned system state information; standardizing the obtained information respectively; processing the standardized information through a deep neural network to obtain a probability value of a selection action; selecting an action according to the obtained probabilityvalue, observing new environment information and obtaining an action evaluation value; collecting all data of interaction between the unmanned system and the environment to train a deep neural network; and performing unmanned system cluster control by using the trained deep neural network. The method is applied to the technical field of unmanned system cluster control.

Description

technical field [0001] The invention relates to the technical field of unmanned system cluster control, and is an unmanned system cluster control method based on deep reinforcement learning. Background technique [0002] Deep learning DL (Deep Learning) is deep learning, which is a kind of method in machine learning methods. Among them, depth means deep neural network, which is a complex network system that simulates the function of human brain neural network by extensive interconnection of a large number of simple processing units. It is a highly complex nonlinear dynamic learning system. The neural network model is described based on the mathematical model of neurons, which can approximate any complex nonlinear function. Deep learning is to learn the internal laws and representation levels of sample data. The information obtained during the learning process is of great help to the interpretation of data such as text, images and sounds. Its ultimate goal is to enable mach...

Claims

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Application Information

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IPC IPC(8): G05D1/02
CPCG05D1/0223G05D1/0221G05D1/0276
Inventor 白成超贾涛何炬恒郭继峰颜鹏郑红星
Owner HARBIN INST OF TECH
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