Novel unmanned aerial vehicle group brain-computer cooperative intelligent control method

Abstract

The invention discloses a novel unmanned aerial vehicle group brain-computer cooperative intelligent control method. Specifically, task states are distinguished by collecting EEG of the brain when anoperator selects or decides, and a computer processes data to extract features and then provides a cluster control strategy to achieve brain-computer coordination. EEG is collected when an operator makes a decision or selects; data processing is carried out by the computer to extract features for classification and identification; an intelligent control strategy is provided in the form of an instruction to inform a fleet operator of the intention, the fleet autonomously cooperates to complete the conversion of the formation mode, the formation mode conversion does not need the operator to makea selection or decision, the burden of the brain is reduced, and the brain-computer division is clear, mutually cooperates and closely cooperates to complete the flight task. The invention aims to provide a new method capable of managing and interacting with the cluster, the defects in the prior art are effectively compensated, human brain intelligence is combined with artificial intelligence, and intelligent control of tasks such as flight formation mode conversion of the unmanned aerial vehicle cluster is realized through brain-computer cooperation.

Description

technical field [0001] The invention belongs to the interdisciplinary research field of brain science, artificial intelligence and unmanned system control. Background technique [0002] The present invention relates to a new method of brain-computer cooperative intelligent control of UAV groups. Through the mutual cooperation and close cooperation of human brain intelligence and artificial intelligence, the UAV group formation is jointly controlled to complete complex tasks. The computer mainly performs a large amount of data processing work, while the human brain Responsible for tasks that are difficult for computers to complete in some cases, such as selection, decision-making, and evaluation. This technology has broad application prospects in aviation, aerospace and other fields, such as fire protection, emergency rescue of natural disasters, remote monitoring, geographic surveying and mapping, etc. [0003] After decades of development, UAV swarm intelligent control tec...

AI Technical Summary

Problems solved by technology

[0003] After decades of development, UAV swarm intelligent control technology has been widely valued and applied. UAV technology has gradually matured. The task of single UAV is far from meeting the needs of production and life in reality. The development of UAV formation technology It has solved this situation, and its advantages such as wide working range and strong task execution ability are far beyond the reach of a single UAV, but there are also problems in the process of controlling the fleet: the existing UAV swarm The control technology is completely based on artificial intelligence, mainly based on intelligent control strategies, that is, the fleet is performing flight missions according to intelligent navigation instructions, artificial intelligence technology cannot cope with unscheduled situations, and the corresponding formation mode cannot be pre-set for unknown environments. There are bound to be dangers in the process of flying according to the established route, so the fleet does not have the ability to adapt to unknown environments, and the risk of collision and crash must exist

[0007] (1) Poor interactivity and no ability to adapt to unknown environments. When using intelligent control strategies to control the fleet, there is no good interaction between the operator and the UAV. Set the corresponding formation mode, because the fleet does not have the ability to adapt to unknown environments, there is a risk of collision and crash

[0008] (2) The task completion ability is poor and the brain burden is heavy. A single UAV control through brain-computer interface technology cannot meet the needs of actual production and life, and long-term control is likely to cause brain fatigue

[0009] (3) Information interaction and delay problems in the cluster communication network, there are a large number of frequent information interactions and time delays in the cluster control process

[0010] The new method of brain-computer collaborative intelligent control of UAV swarms proposed by the present invention can effectively overcome the above problems, and proposes a new approach for intelligent control of UAV swarms. There is no related research in China at present.

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