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Robot behavior decision-making method and device based on memory sequence playback mechanism

A mechanism and sequence technology, applied in the field of robot behavior decision-making, to achieve the effect of improving the convergence speed

Pending Publication Date: 2021-11-02
ZHENGZHOU UNIV
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  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

[0005] One purpose of this application is to provide a robot behavior decision-making method and equipment based on the memory sequence playback mechanism to solve the problem in the prior art of how to achieve the robot's global optimal decision-making through autonomous learning and rapid convergence in a complex environment

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  • Robot behavior decision-making method and device based on memory sequence playback mechanism
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  • Robot behavior decision-making method and device based on memory sequence playback mechanism

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Embodiment Construction

[0046] The present application will be described in further detail below with reference to the accompanying drawings.

[0047] In a typical configuration of the present application, the terminal, the device serving the network, and the trusted party all include one or more processors (eg, a central processing unit (CPU), an input / output interface, a network interface, and a memory).

[0048] Memory may include non-persistent memory in computer readable media, random access memory (RAM) and / or non-volatile memory, such as read only memory (ROM) or flash memory (flash). RAM). Memory is an example of a computer-readable medium.

[0049] Computer-readable media includes both persistent and non-permanent, removable and non-removable media, and storage of information may be implemented by any method or technology. Information may be computer readable instructions, data structures, modules of programs, or other data. Examples of computer storage media include, but are not limited ...

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Abstract

The invention provides a robot behavior decision-making method and device based on a memory sequence playback mechanism, and the method comprises the steps: obtaining a target task and current environment information, wherein the current environment information comprises all obstacle information; constructing a neural network model, setting a dynamic adaptive competition mechanism in a development network, adding an advanced feature presentation layer to carry out online autonomous learning, and continuously updating synaptic connection weights of action neurons in an output layer based on a memory sequence playback mechanism until the network is stable; on the basis of the current environment information, obtaining a global optimal behavior decision through calculation of the neural network model, that is, the method can autonomously learn or identify information of irregular obstacles in a complex environment in online and offline states, so that the robot can adapt to a complex and changeable environment, the global optimal decision of the robot is realized, and the convergence speed of the neural network is improved.

Description

technical field [0001] The present application relates to the field of computers, and in particular, to a robot behavior decision-making method and device based on a memory sequence playback mechanism. Background technique [0002] In the prior art, in the field of robot decision-making optimization, there are a large number of intelligent algorithms, such as ant colony algorithm, immune algorithm, genetic algorithm, particle swarm algorithm, etc., these methods all have task determination, poor intelligent scalability, and cannot adapt to changing environments. And it is difficult to guarantee the global optimality and other limitations. In order to overcome these shortcomings, inspired by the human brain's nervous system, memory mechanism and its information processing mechanism, researchers have proposed a variety of biologically inspired cognitive computing models, which provide opportunities for realizing higher-level cognition and breaking through the limitations of tr...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G05B13/04G06N3/04G06N3/063G06N3/08
CPCG05B13/042G06N3/088G06N3/04G06N3/063
Inventor 王东署罗勇辛健斌王河山马天磊张方方
Owner ZHENGZHOU UNIV
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