Robot task knowledge self-generation system based on virtual demonstration

A technology for generating systems and robots, applied in knowledge expression, instruments, computer parts, etc., can solve the problem of robot task knowledge construction not having universality and interpretability, and achieve enhanced robustness, adaptability, and strong interpretability. , easy to transplant effect

Pending Publication Date: 2021-12-10
TONGJI UNIV
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Problems solved by technology

[0004] The purpose of the present invention is to provide a robot task knowledge self-generation system based on virtual demonstration in order to overcome the

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  • Robot task knowledge self-generation system based on virtual demonstration
  • Robot task knowledge self-generation system based on virtual demonstration
  • Robot task knowledge self-generation system based on virtual demonstration

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[0036] The invention will be described in detail below with reference to the accompanying drawings and specific examples. The present embodiment is implemented in terms of the technical solution of the present invention, and a detailed embodiment and a specific operation process are given, but the scope of the present invention is not limited to the following examples.

[0037] This embodiment is based on the Unity 3D gaming simulation platform, providing a virtual demo-based robot task knowledge self-generation system, specific structural function diagram, for example, by HTC Vive Pro devices. figure 1 As shown, including the abstract semantic rule generation module 1 and the online operation segmentation identification module 2:

[0038] The abstract semantic rule generating module 1 includes a virtual presentation unit 11, an abstract semantic extracting unit 12, and a human activity semantic rule generating unit 13. The virtual presentation unit 11 converts the action in the v...

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Abstract

The invention relates to a robot task knowledge self-generation system based on virtual demonstration. The robot task knowledge self-generation system comprises an abstract semantic rule generation module and an online action segmentation recognition module. The abstract semantic rule generation module comprises a virtual demonstration unit, an abstract semantic extraction unit and a human activity semantic rule generation unit. Actions of human beings in a virtual space are converted into task data, semantic information is extracted according to the task data, and a task semantic rule model is generated according to the semantic information in combination with an action type. The online action segmentation and recognition module comprises a knowledge base unit, a directed probability task graph unit and an action processing unit, and is used for segmenting and recognizing actions according to a task semantic rule model and generating a task graph according to a recognition result. Compared with the prior art, the method has the advantages of being high in interpretability, wide in universality, comprehensive in information and the like.

Description

Technical field [0001] The present invention relates to the field of robotics construction and skill learning, in particular, involving a virtual demo-based robot task knowledge self-generating system. Background technique [0002] With the increasingness of computer, automation, robot technology has developed rapidly. The application of industrial robots has expanded with the transformation and upgrading of manufacturing, and the intelligence of deployment programming of industrial robots has put forward very high requirements. Therefore, it is especially important for the task knowledge of robots. [0003] In fact, human beings have accumulated a lot of knowledge and experience in daily work, and robots' knowledge and skill learning are often related to this. In recent years, the knowledge construct of robots mainly teaches programming, which transforms the teaching information into robotics and motion operation parameters, so that the robot has completed the corresponding oper...

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Application Information

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IPC IPC(8): G06N5/02G06K9/62G06N3/04G06N3/08
CPCG06N5/022G06N3/08G06N3/084G06N3/047G06N3/044G06F18/2414G06F18/2415
Inventor 周艳敏贺睿远蒋荣何斌王志鹏
Owner TONGJI UNIV
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