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Robot functional module granularity division evaluating method based on D-S evidence theory

A technology of functional modules and evidence theory, which is applied in the field of granularity division and evaluation of robot function modules based on D-S evidence theory, and can solve the problems of less research on the evaluation of various module division schemes and decision-making criteria

Inactive Publication Date: 2016-10-12
BEIJING UNIV OF TECH
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Problems solved by technology

However, the above studies mainly focus on the discussion of module division methods, and there are relatively few studies on the evaluation and decision-making criteria of various module division schemes.

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  • Robot functional module granularity division evaluating method based on D-S evidence theory
  • Robot functional module granularity division evaluating method based on D-S evidence theory
  • Robot functional module granularity division evaluating method based on D-S evidence theory

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Embodiment Construction

[0078] The present invention will be further described below in conjunction with the accompanying drawings and specific embodiments.

[0079] The invention realizes the granularity division of the functional modules of the robot control system on the basis of the fuzzy clustering algorithm, and proposes a granularity division evaluation method based on the D-S evidence theory for the optimization problem of the divisional granularity. The flow chart of the method involved is attached figure 1 As shown, the specific implementation process is divided into the following steps:

[0080] Step 1: Divide the functional modules of the intelligent service robot system according to the basic functions and structures, and then obtain the most fine-grained module set.

[0081] Step 2: Refer to Table 6 to conduct a pairwise analysis of the elements in the module set to obtain the functional correlation matrix and structural correlation matrix of the functional modules of the robot system...

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Abstract

The invention discloses a robot functional module granularity division evaluating method based on a D-S evidence theory and belongs to the field of robot decentralized control. The method mainly comprises four steps of: creating a relation measure index among the functional modules and a relation measure index in each functional module in virtue of a principle that functional modules of a smart service robot system are independent, and solving a cohesion degree utility value and a coupling degree utility value of each model division scheme in combination with a correlation measure matrix; constructing a multi-attribute decision matrix by using the cohesion degree and the coupling degree as two evidence sources of the evidence theory, and introducing the concept of a membership function in order to transform the utility value in the decision matrix; solving the utility assigned value of each focal element in combination with the definition of a basic probability assigned value, and synthesizing the preference information with different attributes of each scheme to construct a trust interval; and ordering the decision schemes on the basis of an interval number preference ordering method in order to obtain the optimal division granularity of each functional module of the smart service robot system.

Description

technical field [0001] The invention belongs to the field of decentralized control of robots. Combining with the module division scheme of the robot control system, the invention particularly relates to a method for evaluating the granularity division of robot function modules based on the D-S evidence theory. Background technique [0002] In recent years, with the rapid development of intelligent service robot research, robot modular control technology has attracted more and more researchers' attention. As a key technology in distributed control system research, module granularity division can effectively shorten the development cycle and improve the flexibility of the system. How to evaluate the module division schemes under different granularities, and then select the optimal scheme is an urgent problem to be solved in robot modularization technology. [0003] The division of functional modules of intelligent service robots is a clustering process. The current division s...

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Application Information

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IPC IPC(8): G06N5/04G06K9/62
CPCG06N5/04G06F18/2323
Inventor 贾松敏张国梁丁明超李秀智李柏杨
Owner BEIJING UNIV OF TECH
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