Intelligent robot with emotion adjusting function
By integrating emotion recognition, calculation, diagnosis and control modules in intelligent robots, the problem of insufficient emotional services for human-computer interaction in the prior art is solved, the recognition and adjustment of emotional states is realized, and the naturalness of human-computer interaction and emotional service capabilities are improved.
Patent Information
- Application Number
- CN202510356056.9
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-03-25
- Publication Date
- 2025-07-04
AI Technical Summary
Existing intelligent robots have not yet met human expectations in terms of emotional services for human-computer interaction, and lack effective emotional computing models and complete human-computer interaction processes.
Design an intelligent robot, including emotion recognition module, emotion calculation module, emotion diagnosis module and emotion control module, collect data through Internet of Things devices, establish an emotion computing model, identify and regulate human emotional state, and provide emotional services.
It realizes the identification, prediction and regulation of human emotions, improves the naturalness of human-computer interaction and emotional service capabilities, can quantitatively describe the internal laws of emotional transformation, and provides emotional control suggestions.
Smart Images
Figure CN120258038A_ABST
Abstract
Description
Technical Field
[0001] The present invention belongs to the technical field of affective computing in artificial intelligence, and particularly relates to an intelligent robot with an emotion regulation function. Background Art
[0002] With the development of artificial intelligence technology, intelligent robots have achieved remarkable results in fields such as game reasoning, military reconnaissance, and industrial labor. While people marvel at the excellent performance of intelligent robots in logical reasoning and auxiliary labor, they are also gradually exploring the possibility of intelligent robots serving human emotions.
[0003] However, the current research results are far from satisfactory. These robots have not reached the level of strong artificial intelligence with perception and self-awareness. In other words, emotional robots can have strong computing and reasoning abilities, but there is still a large gap from human expectations in terms of emotional services in human-computer interaction. To achieve a more natural human-computer interaction experience and improve the emotional service ability of intelligent robots, a key challenge is to establish a quantifiable affective computing model and design a complete human-computer interaction process to complete the emotional service function of intelligent robots. Summary of the Invention
[0004] (1) Technical Problems to be Solved
[0005] The technical problem to be solved by the present invention is: how to provide an intelligent robot with an emotion regulation function.
[0006] (2) Technical Solutions
[0007] To solve the above technical problems, the present invention provides an intelligent robot with an emotion regulation function, and the intelligent robot includes: an emotion recognition module, an emotion calculation module, an emotion diagnosis module, and an emotion control module;
[0008] The emotion recognition module is used to recognize the current emotional state of the experimental object during the human-computer interaction process;
[0009] The emotion calculation module is used to collect data on facial expressions, postural expressions, intonation expressions, and behaviors, and then calculate the active energy of each of the four basic emotions of the experimental object at this moment: happiness, anger, anxiety, and fear, and establish an affective computing model with random perturbations;
[0010] The emotion diagnosis module is used to comprehensively evaluate the emotional health status according to the results of emotion calculation; establish a health standard line to judge whether the experimental object needs emotion control;
[0011] The emotion control module is used to implement emotion control based on the calculation of the emotion calculation model.
[0012] Among them, the emotion recognition module is used to recognize the current emotional state of the experimental subject during the human-computer interaction process; in order to accurately recognize the current emotional state of the experimental subject, auxiliary Internet of Things devices are pre-deployed for comprehensive data collection. The emotion recognition module analyzes and learns a large amount of data of the experimental subject from the Internet of Things devices, and obtains its current emotional state according to specific artificial intelligence algorithms.
[0013] Among them, the Internet of Things devices for comprehensive data collection include smart watches, smart treadmills, and smart phones.
[0014] Among them, according to modern emotion theory, the emotional states of humans include four basic emotions: happiness, anger, anxiety, and fear. Other complex emotions are the results of the integration of these four basic emotions; these four emotional states are caused by the stimulation of external events.
[0015] The emotion calculation module is used to collect data on facial expressions, posture expressions, intonation expressions, and behaviors, and then calculate the active energy of each of the four basic emotions of the experimental subject at this moment: happiness, anger, anxiety, and fear.
[0016] Suppose the emotion calculation module calculates that the emotional state of the experimental subject at time t is X(t) = [x1(t), x2(t), x3(t), x4(t)] T , where x i (t) represents the estimation of the emotional state of the four basic emotions; i is the serial number of the basic emotion, i = 1, 2, 3, 4.
[0017] To establish an accurate model to describe the evolution of these four emotions, first, according to the two-dimensional emotion model theory, analyze their internal properties: classify happiness as a positive emotional state, which is beneficial to human health; on the contrary, define anger, anxiety, and fear as negative emotional states, which are harmful to human health; among them, happiness is opposite to the other three emotions, similar to the competition between species, and has a negative impact on each other; anger, anxiety, and fear are three emotions with gradually increasing degrees of harm to the human body, and the transformation process is from anger to anxiety, and then from anxiety to fear.
[0018] The above relationship is similar to the interaction between different populations in the biological world; in the population dynamics model, differential equations are used to describe the relationships between multiple species: cooperation, competition, and predation; based on the mathematical modeling principle of population ecology, the relationship between the generation and transformation of the four basic emotional states can be used to establish an emotional model of an intelligent robot to quantitatively describe the transformation mechanism between the four basic emotional states; specifically, the emotion calculation module establishes the following calculation model for the emotional transformation of the experimental subject:
[0019]
[0020] Among them, b i represents the emotional state x i (t) of the four basic emotions, meaning that discrete emotions will self-generate in the current environment; a ii represents the self-inhibition coefficient of emotions, which means that the experimental subject has a certain degree of self-inhibition ability for each emotion; a 12 , a 13 and a 14 represent the ability coefficient for positive emotions to transform into negative emotions; a 21 , a 31 and a 41 represent the ability coefficient for negative emotions to transform into positive emotions; a 32 , a 32 , a 34 and a 43 represent the intensity coefficients for the gradual deepening transformation of the three negative emotions;
[0021] An individual's emotions are inevitably affected by the external random environment, including positive, negative, favorable and adverse circumstances; Gaussian white noise is used to quantify the random perturbation, and it is assumed that the random perturbation acts on the self-excitation coefficient b i of the basic emotions, that is, b i +σ i dB i (t) is used to replace b i , i = 1, 2, 3, 4, where B i (t) represents independent standard Brownian motions, and satisfies the storage condition B i (0) = 0, σ i represents the intensity of the random perturbation; substituting the random perturbation into the above formula, the following emotional computing model with random perturbation is obtained:
[0022]
[0023] Among them, the emotion diagnosis module comprehensively evaluates the emotional health status according to the results of emotional computing; an emotional diagnosis function ψ: X(t) → δ is established, where δ ∈ (0, 1); a health standard line θ ∈ (0, 1) is established. When θ ∈ (0, δ), it is in an unhealthy state and emotional control is required. When θ ∈ [δ, 1), it is in a healthy state and no external intervention is needed.
[0024] Among them, the emotion control module is used to achieve emotion control on the basis of the calculation of the emotion calculation model when the experimental subject needs emotion control; psychological research shows that both positive emotions and negative emotions can be appropriately controlled, which includes the positive mobilization of positive emotions and the reverse inhibition of negative emotions; by adding pulse control to the emotion calculation model, an emotion control model is obtained as follows:
[0025]
[0026] Among them, α k , β k , γ k and λ k respectively represent the regulation ratios of four basic emotions; for positive emotions, positive stimulus control is used, and for negative emotions, reverse inhibition control is used; the moment serial number in
[0027] t k represents the time series corresponding to the pulse control; k represents the moment serial number in the time series t k ; represents the value of the left endpoint in the time series t k ;
[0028] Among them, the intelligent robot can provide service functions of emotion recognition, emotion calculation, emotion diagnosis and emotion control during the interaction with people;
[0029] The intelligent robot completes the emotion recognition function in human-computer interaction. Based on the emotion recognition technology of artificial intelligence, the intelligent robot can monitor the experimental subject through Internet of Things devices or directly interact with the experimental subject, and then recognize the current emotional state of the experimental subject.
[0030] Among them, the intelligent robot completes the emotion calculation function in human-computer interaction. After the emotional state, an emotion calculation model with random perturbation is established, which will simulate the law of human emotion change; using the emotion calculation model, it is possible to predict how human emotions will change and when human emotions will reach a stable state.
[0031] Among them, the intelligent robot completes the emotion diagnosis function in human-computer interaction; based on the emotional stable state obtained in the emotion calculation step, emotion diagnosis can be used to judge whether this emotional state is healthy, and then generate a health discrimination index to indicate whether medical treatment is needed; specifically, each human-computer interaction is a kind of psychological diagnosis, and emotion calculation plays the role of a psychologist, making a good or bad judgment on the emotional state of the tester; in the human-computer interaction service, the intelligent robot can not only diagnose emotions, but also take appropriate strategies to control emotions;
[0032] Among them, the intelligent robot completes the emotion control function in human-computer interaction. If the intelligent robot predicts that the host will reach an unhealthy stable state in the short term or long term, then they will execute the control and adjustment of the prediction model until a healthy and satisfactory stable state is reached; then, the intelligent robot will convert the control strategy and intensity of the system into a recommended strategy, which will be fed back to humans for emotion regulation; ultimately, it can be achieved that artificial intelligence serves humans in essence and also serves human emotions.
[0033] (III) Beneficial effects
[0034] Compared with the prior art, the present invention studies the basic laws of emotion evolution, establishes a mathematical model to quantitatively describe the internal laws of various emotion transformations, and endows the algorithm to the emotion robot technology, enabling it to identify and predict changes in human emotion states, and then intervene and regulate human emotions, so as to achieve the machine serving human emotions. This will be the core function of the intelligent robot of the present invention and also an important breakthrough in realizing that the intelligent robot provides services for human emotions. BRIEF DESCRIPTION OF THE DRAWINGS
[0035] Figure 1 It is a schematic diagram of human-computer interaction of the present inventor.
[0036] Figure 2 It is a diagram of the transformation relationship of four basic emotions
[0037] Figure 3 It is a diagram of human-computer interaction data acquisition. DETAILED DESCRIPTION OF THE INVENTION
[0038] To make the objectives, contents, and advantages of the present invention clearer, the following further describes in detail the specific embodiments of the present invention with reference to the drawings and embodiments.
[0039] To solve the above technical problems, the present invention provides an intelligent robot with an emotion regulation function, and the intelligent robot includes: an emotion recognition module, an emotion calculation module, an emotion diagnosis module, and an emotion control module;
[0040] The emotion recognition module is used to recognize the current emotion state of the experimental object during human-computer interaction;
[0041] The emotion calculation module is used to collect data on facial expressions, posture expressions, intonation expressions, and behaviors, and then calculate the active energy of each of the four basic emotions of the experimental object at this moment: happiness, anger, anxiety, and fear, and establish an emotion calculation model with random perturbations;
[0042] The emotion diagnosis module is used to comprehensively evaluate the emotion health status according to the results of emotion calculation; establish a health standard line to judge whether the experimental object needs emotion control;
[0043] The emotion control module is used to achieve emotion control based on the calculation of the emotion computing model.
[0044] Among them, the emotion recognition module is used to recognize the current emotional state of the experimental subject during the human-computer interaction process; in order to accurately recognize the current emotional state of the experimental subject, auxiliary Internet of Things devices are pre-deployed for comprehensive data collection. The emotion recognition module analyzes and learns a large amount of data of the experimental subject from the Internet of Things devices, and obtains its current emotional state according to specific artificial intelligence algorithms.
[0045] Among them, the Internet of Things devices for comprehensive data collection include smart watches, smart treadmills, and smart phones.
[0046] Among them, according to modern emotion theory, the emotional states of humans include four basic emotions: happiness, anger, anxiety, and fear. Other complex emotion checks are the results of the integration of the four basic emotions; these four emotional states are caused by the stimulation of external events;
[0047] The emotion computing module is used to collect data on facial expressions, posture expressions, intonation expressions, and behaviors, and then calculate the active energy of each of the four basic emotions of the experimental subject at this moment: happiness, anger, anxiety, and fear.
[0048] Suppose the emotion computing module calculates that the emotional state of the experimental subject at time t is X(t) = [x1(t), x2(t), x3(t), x4(t)] T , where x i (t) represents the estimation of the emotional state of the four basic emotions; i is the serial number of the basic emotion, i = 1, 2, 3, 4;
[0049] Establish an accurate model to describe the evolution of these four emotions. First, according to the two-dimensional emotion model theory, analyze their internal properties: classify happiness as a positive emotional state, which is beneficial to the health of the human body; on the contrary, define anger, anxiety, and fear as negative emotional states, which are harmful to the health of the human body; among them, happiness is opposite to the other three emotions, similar to the competition between species, and has a negative impact on each other; anger, anxiety, and fear are three emotions with gradually increasing degrees of harm to the human body, and the transformation process is from anger to anxiety, and then from anxiety to fear.
[0050] The above relationship is similar to the interaction between different populations in the biological world; in the population dynamics model, differential equations are used to describe the relationships among multiple species: cooperation, competition, and predation; based on the mathematical modeling principle of population ecology, a relationship between the generation and transformation of four basic emotional states can be used to establish an emotional model for intelligent robots to quantitatively describe the transformation mechanism among the four basic emotional states; specifically, the emotion calculation module has established the following calculation model for the emotion transformation of the experimental object:
[0051]
[0052] where b i represents the self-growth coefficient of the emotional state x i (t) of the four basic emotions, meaning that discrete emotions will self-generate in the current environment; a ii represents the self-inhibition coefficient of emotions, which means that the experimental object has a certain degree of self-inhibition ability for each emotion; a 12 , a 13 and a 14 represent the ability coefficients for positive emotions to transform into negative emotions; a 21 , a 31 and a 41 represent the ability coefficients for negative emotions to transform into positive emotions; a 32 , a 32 , a 34 and a 43 represent the intensity coefficients for the gradual deepening transformation of the three negative emotions;
[0053] An individual's emotions are inevitably affected by the external random environment, including positive, negative, favorable, and adverse circumstances; Gaussian white noise is used to quantify the random perturbation, and it is assumed that the random perturbation acts on the self-excitation coefficient b i of the basic emotions, that is, b i +σ i dB i (t) is used to replace b i , i = 1, 2, 3, 4, where B i (t) represents independent standard Brownian motions and satisfies the storage condition B i (0) = 0, and σ i represents the intensity of the random perturbation; substituting the random perturbation into the above formula, the following emotion calculation model with random perturbation is obtained:
[0054]
[0055] Among them, the emotion diagnosis module comprehensively evaluates the emotional health status according to the results of emotion calculation; an emotion diagnosis function ψ: X(t)→δ is established, where δ∈(0,1); a health standard line θ∈(0,1) is established. When θ∈(0,δ), it is in an unhealthy state and emotion control is required. When θ∈[δ,1), it is in a healthy state and no external intervention is needed.
[0056] Among them, the emotion control module is used to achieve emotion control based on the calculation of the emotion calculation model when the experimental object needs emotion control; psychological research shows that both positive emotions and negative emotions can be appropriately controlled, which includes the positive mobilization of positive emotions and the reverse inhibition of negative emotions; by adding pulse control to the emotion calculation model, an emotion control model is obtained as follows:
[0057]
[0058] Among them, α k , β k , γ k and λ k respectively represent the regulation ratios of four basic emotions; for positive emotions, positive stimulus control is used, and for negative emotions, reverse inhibition control is used; the moment serial number in;
[0059] t k represents the time series corresponding to the pulse control; k represents the moment serial number in the time series t k in; represents the value of the left endpoint in the time series t k ;
[0060] Among them, the intelligent robot can provide service functions of emotion recognition, emotion calculation, emotion diagnosis and emotion control during the interaction with people;
[0061] The intelligent robot completes the emotion recognition function in human-computer interaction. Based on the emotion recognition technology of artificial intelligence, the intelligent robot can monitor the experimental object through Internet of Things devices or directly interact with the experimental object, and then recognize the current emotion state of the experimental object.
[0062] Among them, the intelligent robot completes the emotion calculation function in human-computer interaction. After the emotion state, an emotion calculation model with random perturbation is established, which will simulate the law of human emotion change; using the emotion calculation model, it is possible to predict how human emotions will change and when human emotions will reach a stable state.
[0063] Among them, the intelligent robot completes the emotion diagnosis function in human-computer interaction; based on the emotional stability state obtained in the emotional computing step, the emotion diagnosis can be used to judge whether this emotional state is healthy, and then generate a health discrimination index to indicate whether medical treatment is needed; specifically, each human-computer interaction is a kind of psychological diagnosis, and emotional computing plays the role of a psychologist, making a good or bad judgment on the emotional state of the test subject; in the human-computer interaction service, the intelligent robot can not only diagnose emotions, but also adopt appropriate strategies to control emotions;
[0064] Among them, the intelligent robot completes the emotion control function in human-computer interaction. If the intelligent robot predicts that the host will reach an unhealthy stable state in the short term or long term, then they will execute the control and adjustment of the prediction model until a healthy and satisfactory stable state is reached; then, the intelligent robot will convert the control strategy and intensity of the system into a recommended strategy, which will be fed back to humans for emotion regulation; ultimately, it can be realized that artificial intelligence serves humans in essence and also serves human emotions.
[0065] Embodiment 1
[0066] As Figure 1 shown, it is the human-computer interaction architecture of the present invention, which can complete the human-computer interaction between an experimental subject and an intelligent robot. The emotional robot on the right can complete the functions of emotion recognition, emotion computing, emotion diagnosis and emotion control. On the terminal display interface, emotional data, prediction curves and suggestions can be displayed. The experimental subject on the left can be summarized into four main emotions: happiness, anger, anxiety and fear, and the mutual conversion relationship of the four emotions is as Figure 2 shown.
[0067] Step 1: Data collection. The data collection process in human-computer interaction is as Figure 3 shown. After starting the human-computer interaction, the intelligent robot can obtain its data directly from the experimental subject, and also obtain data through Internet of Things devices (such as smart watches, treadmills, smart watches, smart cameras, etc.).
[0068] Step 2: Data analysis and parameter determination. The intelligent machine analyzes and mines the emotional state of the current experimental subject from the large amount of raw data obtained according to specific artificial intelligence algorithms. In the interaction with a specific experimental subject, the intelligent robot can identify the emotional state components x1(t), x2(t), x3(t) and x4(t) at the current moment, and it is necessary to determine b T and a i in the emotion computing model according to the continuous emotion change law {X(t) = [x1(t), x2(t), x3(t), x4(t)] ij , t ∈ (t1, t2)}.
[0069] Step 3: Emotional computing. Take the initial value state X(t) = [x1(t), x2(t), x3(t), x4(t)] determined in Step 2 T , the model parameters b i and a ij , as the specific model for the emotional computing of the experimental subject, and perform emotional computing according to the algorithm of model formula (2), then the emotional state change curve of the experimental subject within a time period (t0, t) can be given.
[0070] Step 4: Emotional diagnosis. Grab the emotional state X(t + nT) = [x1(t + nT), x2(t + nT), x3(t + nT), x4(t + nT)] within the time period (t0, t) at a fixed period T T as the input of the emotional diagnosis function, calculate ψ[X(t + nT)]. If θ ∈ (0, δ), it means the emotional state is healthy and no intervention is required; if θ ∈ [δ, 1); it means the emotional state is unhealthy and emotional control needs to be performed, and determine the control intensity α k , β k , γ k and λ k ; n is the number of cycles.
[0071] Step 5: Emotional control. Take the latest emotional state X(t) = [x1(t), x2(t), x3(t), x4(t)] T and the control intensity α k , β k , γ k and λ k as the input of model formula (2). After T cycles, continue to execute Step 4 to calculate ψ[X(t + nT)]. Each time pulse control is executed, α k , β k , γ k and λ k need to be converted into actionable behaviors for the experimental subject (such as listening to a piece of music, going for a run, etc.) through the semantic conversion module.
[0072] Using the intelligent robot of the present invention, an emotional computing and emotional control model with subject characteristics can be provided for each experimental subject, that is, different model parameters are established according to different individual characteristics. Using the intelligent robot of the present invention can be used as a dedicated emotional regulation expert for an individual, prescribing the right medicine and timely regulating, providing a complete new method for realizing the service of intelligent robots for human emotions.
[0073] The above are only the preferred embodiments of the present invention. It should be noted that for those of ordinary skill in the art, without departing from the technical principle of the present invention, several improvements and modifications can be made, and these improvements and modifications should also be regarded as the protection scope of the present invention.
Claims
1. An intelligent robot with an emotion regulation function, characterized in that, The intelligent robot includes: an emotion recognition module, an emotion calculation module, an emotion diagnosis module, and an emotion control module; The emotion recognition module is used to recognize the current emotional state of the experimental subject during human-computer interaction; The emotion calculation module is used to collect data on facial expressions, posture expressions, intonation expressions, and behaviors, and then calculate the active energy of each of the four basic emotions of the experimental subject at this moment: happiness, anger, anxiety, and fear, and establish an emotion calculation model with random perturbations; The emotion diagnosis module is used to comprehensively evaluate the emotional health status based on the results of emotion calculation; establish a health standard line to determine whether the experimental subject needs emotion control; The emotion control module is used to achieve emotion control based on the calculation of the emotion calculation model.
2. The intelligent robot with an emotion regulation function according to claim 1, wherein, The emotion recognition module is used to recognize the current emotional state of the experimental subject during human-computer interaction; in order to accurately recognize the current emotional state of the experimental subject, auxiliary Internet of Things devices are pre-deployed for comprehensive data collection. The emotion recognition module analyzes and learns a large amount of data of the experimental subject from the Internet of Things devices, and obtains its current emotional state according to specific artificial intelligence algorithms.
3. The intelligent robot with an emotion regulation function according to claim 2, wherein, The Internet of Things devices for comprehensive data collection include smart watches, smart treadmills, and smart phones.
4. The intelligent robot with an emotion regulation function according to claim 2, characterized in that, The emotion calculation module is used to collect data on facial expressions, posture expressions, intonation expressions, and behaviors, and then calculate the active energy of each of the four basic emotions of the experimental subject at this moment: happiness, anger, anxiety, and fear; Suppose the emotion computing module calculates that the emotional state of the experimental subject at time t is X(t) = [x1(t), x2(t), x3(t), x4(t)] T , where x i (t) represents the estimated value of the emotional state of the four basic emotions; i is the serial number of the basic emotion, i = 1, 2, 3, 4; Establish an accurate model to describe the evolution of these four emotions. First, according to the two-dimensional emotion model theory, analyze their internal attributes: classify happiness as a positive emotional state, which is beneficial to human health; on the contrary, define anger, anxiety, and fear as negative emotional states, which are harmful to human health; among them, happiness is opposed to the other three emotions, similar to the competition between species, and has a negative impact on each other; anger, anxiety, and fear are three emotions with gradually increasing degrees of harm to the human body, and the transformation process is from anger to anxiety, and then from anxiety to fear; The above relationship is similar to the interaction between different populations in the biological world; in the population dynamics model, differential equations are used to describe the relationships between multiple species: cooperation, competition, predation; based on the mathematical modeling principle of population ecology, the relationship between the generation and transformation of the four basic emotional states can be used to establish an emotion model of the intelligent robot to quantitatively describe the transformation mechanism between the four basic emotional states; specifically, the emotion calculation module establishes the following calculation model for the emotion transformation of the experimental subject: Among them, b i represents the emotional state x i (t) of the four basic emotions, which means that discrete emotions will self-generate in the current environment; a ii represents the self-inhibition coefficient of emotions, which means that the experimental subject has a certain degree of self-inhibition ability for each emotion; a 12 , a 13 and a 14 represent the ability coefficient for positive emotions to transform into negative emotions; a 21 , a 31 and a 41 represent the ability coefficient for negative emotions to transform into positive emotions; a 32 , a 32 , a 34 and a 43 represent the intensity coefficients for the gradual deepening transformation of the three negative emotions; An individual's emotions are inevitably affected by the external random environment, including positive, negative, favorable and adverse circumstances; Gaussian white noise is used to quantify the random perturbation, and it is assumed that the random perturbation acts on the self-excitation coefficient b of the basic emotion i above, that is, b i +σ i dB i (t) is used to replace b i , i = 1, 2, 3, 4, where B i (t) represents independent standard Brownian motions and satisfies the storage condition B i (0) = 0, σ i represents the intensity of the random perturbation; substituting the random perturbation into the above formula, the following emotion calculation model with random perturbation is obtained:
5. The intelligent robot with an emotion regulation function according to claim 4, characterized in that, The emotion diagnosis module comprehensively evaluates the emotional health status based on the results of emotion calculation; establish an emotion diagnosis function ψ: X(t)→δ, where δ∈(0,1); establish a health standard line θ∈(0,1). When θ∈(0,δ), it is in an unhealthy state and requires emotion control. When θ∈[δ,1), it is in a healthy state and does not require external intervention.
6. The intelligent robot with an emotion regulation function according to claim 5, characterized in that, The described emotion control module is used to achieve emotion control based on the calculation of an emotion computing model when the experimental subject needs emotion control; psychological research shows that both positive and negative emotions can be appropriately controlled, which includes the positive mobilization of positive emotions and the reverse inhibition of negative emotions; by adding pulse control to the emotion computing model, an emotion control model is obtained as follows: Among them, α k , β k , γ k and λ k respectively represent the regulation ratios of four basic emotions; for positive emotions, positive stimulus control is used, and for negative emotions, reverse inhibitory control is used; the moment serial numbers in t k represents the time series corresponding to pulse control; k represents the sequence number of the moment in the time series t k ; represents the value of the left endpoint in the time series t k .
7. The intelligent robot with an emotion regulation function according to claim 6, characterized in that, The described intelligent robot can provide service functions of emotion recognition, emotion computing, emotion diagnosis, and emotion control during the interaction with humans; The described intelligent robot completes the emotion recognition function in human-computer interaction. Based on the emotion recognition technology of artificial intelligence, the intelligent robot can monitor the experimental subject through Internet of Things devices or directly interact with the experimental subject, and then recognize the current emotional state of the experimental subject.
8. The intelligent robot with an emotion regulation function according to claim 6, wherein, The described intelligent robot completes the emotion computing function in human-computer interaction. After the emotional state, an emotion computing model with random perturbations is established, which will simulate the law of human emotion changes; Using the emotion computing model, it is possible to predict how human emotions will change and when human emotions will reach a stable state.
9. The intelligent robot with an emotion regulation function according to claim 6, wherein, The described intelligent robot completes the emotion diagnosis function in human-computer interaction; based on the emotional stable state obtained in the emotion computing step, emotion diagnosis can be used to judge whether this emotional state is healthy, and then generate a health discrimination index to indicate whether medical treatment is needed; Specifically, each human-computer interaction is a kind of psychological diagnosis, and emotion computing plays the role of a psychologist, making a good or bad judgment on the emotional state of the tester; in the human-computer interaction service, the intelligent robot can not only diagnose emotions but also adopt appropriate strategies to control emotions.
10. The intelligent robot with an emotion regulation function according to claim 6, characterized in that, The described intelligent robot completes the emotion control function in human-computer interaction. If the intelligent robot predicts that the host will reach an unhealthy stable state in the short term or long term, then they will execute the control and adjustment of the prediction model until a healthy and satisfactory stable state is reached; then, the intelligent robot will convert the control strategy and intensity of the system into a recommended strategy, which will be fed back to humans for emotion regulation; ultimately, it can be realized that artificial intelligence serves humans in essence and also serves human emotions.