Behavior pattern learning system for augmentor

A pattern learning and robot technology, applied in the direction of instruments, manipulators, program control manipulators, etc., to achieve the effect of increasing affinity

Inactive Publication Date: 2017-03-29
深圳量旌科技有限公司
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] However, at present, the stand-in robot can only express the relatively friendly and real behavior pattern of ...

Method used

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Embodiment Construction

[0021] In order to make the object, technical solution and advantages of the present invention clearer, the present invention will be further described in detail below in conjunction with the accompanying drawings and specific embodiments. It should be understood that the specific embodiments described here are only used to explain the present invention, and are not intended to limit the present invention.

[0022] see Figure 1-2 , a behavior pattern learning system for a stand-in robot, which includes an intelligent terminal, a stand-in robot interaction system, and a stand-in human behavior subsystem;

[0023] see figure 1 , during online learning of the stand-in behavior pattern: the smart terminal includes motion control input, camera one, microphone one, display screen one, speaker one, camera one, microphone one to collect the expression and voice of the stand-in person, display screen one and speaker A pair of stand-ins for image and voice expression;

[0024] The s...

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Abstract

The invention discloses a behavior pattern learning system for an augmentor, and relates to the technical field of a robot control system. An intelligent terminal comprises an action control input part, a camera I, a microphone I, a display screen I, a loudspeaker I, and the camera I; an augmentor interaction system comprises robot actions, a display screen II, a loudspeaker II, a camera II and a microphone II; a substituted person behavior sub system comprises an interaction person voice recognition part, an associated syntax database, a language habit library, an expression library, an action library, a substituted person voice recognition part, a language habit training part, a language expression matching training part, and a language action matching training part; a robot performs long-term deep learning on action habits, language habits, expression habits and the like which can express behavior habit characteristics of the substituted person through learning algorithms of a neural network and the like in the use process of the substituted person, so that when the substituted person is not online, the robot still can express behavior characteristics of the substituted person so as to improve the affinity of the augmentor in personification substituting.

Description

technical field [0001] The invention relates to the technical field of robot control systems, in particular to a behavior pattern learning system for a stand-in robot. Background technique [0002] A stand-in robot uses a humanoid robot as a carrier. People control the behavior of the robot through a remote terminal. This control includes video transmission, audio transmission, control logic transmission, etc., so that people can pass through in a very short time even if they are in other places. The substitute robot is used as a carrier to return to the activity place where the robot is located, and use the robot to complete what people want to do, such as accompanying family members and participating in meetings. [0003] However, at present, the stand-in robot can only express the relatively friendly and real behavior pattern of the stand-in person only when the stand-in person is controlled online. A completely different robot interaction experience. In order to solve ...

Claims

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Application Information

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IPC IPC(8): G06F17/30G10L15/26B25J9/16
CPCB25J9/163G06F16/3329G10L15/26
Inventor 招子安
Owner 深圳量旌科技有限公司
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