A method of robot emotion cognition based on deep learning

Abstract

The present invention provides a method for emotional cognition of robots based on deep learning, including: obtaining multi-modal information, obtaining emotional states through multi-modal information fusion algorithms; inputting emotional states into interactive decision-making models for processing to obtain decision-making information, Output the decision information to the satisfaction model; use the satisfaction model to detect whether the decision information output by the interactive decision model conforms to the preferences of the current user, if so, enter the long-term memory, update the data, and update the obtained decision information The information is output to the behavior selector to obtain the robot behavior output; otherwise, the recorded fragments and the corresponding user's emotional changes are obtained from the short-term memory, and the user characteristics are extracted from the long-term memory, and the decision information is calculated by using the LSTM deep learning model. The obtained decision information is output to the behavior selector to obtain the robot behavior output. The invention improves the cognitive ability of the robot through the interactive decision-making model, and better performs human-computer interaction.

Description

technical field [0001] The invention relates to the field of information technology, in particular to a method for robot emotion cognition based on deep learning. Background technique [0002] Judging from the current achievements in robot emotional cognition, calculations are mainly based on physical behavior, and there is no progress in emotional cognition. The existing methods have the following defects: 1. Most of the robots on the market belong to the category of industrial robots, and further human-computer interaction based on human emotion is not considered in the interaction process; 2. All robots have decision-making modules, but none of them are based on emotion And making behavioral decisions is not conducive to the development of social behavior between robots and humans; 3. Existing research rarely has an emotional cognition framework based on deep learning, and cannot interact with different objects, nor can it perform better self-awareness renew. Contents ...

AI Technical Summary

Problems solved by technology

The existing methods have the following defects: 1. Most of the robots on the market belong to the category of industrial robots, and further human-computer interaction based on human emotion is not considered in the interaction process; 2. All robots have decision-making modules, but none of them are based on emotion And making behavioral decisions is not conducive to the development of social behavior between robots and humans; 3. Existing research rarely has an emotional cognition framework based on deep learning, and cannot interact with different objects, nor can it perform better self-awareness renew

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