Intelligent electronic pet system based on artificial intelligence multi-mode interaction and autonomous learning
The intelligent electronic pet system based on artificial intelligence multimodal interaction and self-learning solves the problem of the single interaction method of existing electronic pets, realizes a deeper understanding of user emotions and personalized services, and enhances the emotional connection and interactive experience between users and electronic pets.
Patent Information
- Application Number
- CN202511307352.6
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-09-13
- Publication Date
- 2025-12-16
AI Technical Summary
Existing electronic pets have relatively simple interaction methods, mostly relying on traditional feedback. They cannot fully understand the user's emotions and intentions, nor can they adapt to changes in user behavior and environment, thus failing to meet the diverse needs of users.
The system employs an intelligent electronic pet system based on artificial intelligence multimodal interaction and autonomous learning, including a multimodal interaction module, an emotion computing module, an autonomous learning module, a growth and evolution system, and a physical form and motion control module. By capturing the user's facial expressions, body movements, and physiological signals in real time, it utilizes deep learning and reinforcement learning algorithms to optimize personalized services and interaction strategies, and combines flexible materials and biomimetic motors to achieve natural movement and customized appearance.
This enables electronic pets to understand users' emotions and intentions more deeply, provide personalized services, enhance emotional connections, meet diverse needs, offer rich interactive content and a continuous sense of purpose, and break through the interactive limitations of traditional electronic pets.
Abstract
Description
Technical Field
[0001] This invention relates to the field of artificial intelligence technology, specifically to an intelligent electronic pet system based on artificial intelligence multimodal interaction and autonomous learning. Background Technology
[0002] With the rapid development of artificial intelligence technology, electronic pets, as a new type of digital entertainment and companion product, are gradually attracting people's attention. Traditional electronic pets usually have simple feeding and growth mechanisms, such as upgrades based on online time. This approach lacks deep interaction with users and makes it difficult to establish the close emotional bond like that between a traditional pet and its owner, thus offering limited emotional comfort to users.
[0003] Meanwhile, existing electronic pets have relatively simple interaction methods, mostly relying on simple command input and preset feedback. They cannot fully understand the user's emotions and intentions, nor can they adapt to changes in user behavior and environment. Furthermore, as people's demand for personalized and customized experiences continues to increase, existing electronic pets are struggling to meet the diverse needs of users. Summary of the Invention
[0004] The purpose of this invention is to provide an intelligent electronic pet system based on artificial intelligence multimodal interaction and autonomous learning, which solves the problem that existing electronic pets have relatively simple interaction methods, mostly relying on simple command input and preset feedback, and are unable to fully understand the user's emotions and intentions, and are also difficult to adapt to changes in user behavior and environment.
[0005] To achieve the above objectives, the present invention provides the following technical solution: This intelligent electronic pet system, based on AI-powered multimodal interaction and autonomous learning, includes a multimodal interaction module, an emotion computing module, an autonomous learning module, a growth and evolution system, and a physical form and motion control module. The multimodal interaction module captures the user's facial expressions, body movements, voice features, and physiological signals in real time to comprehensively perceive the user's state. The emotion computing module, based on the data acquired by the multimodal interaction module, uses a deep learning model to identify the user's emotional state and generates emotional response strategies such as playing music, providing comforting voices, and engaging in affectionate gestures. The autonomous learning module learns the user's lifestyle habits and interests using a learning framework, and optimizes interaction strategies using reinforcement learning algorithms to provide personalized services. The growth and evolution system sets up multi-dimensional interactive tasks, rewarding users with corresponding growth performance values based on task completion, and upgrading and evolving functions, appearance, and interaction methods when level update conditions are met. The physical form and motion control module borrows from embodied intelligence technology to achieve life-like movement, conveying emotions through flexible materials and biomimetic motor design, and allowing users to customize the appearance using modular components.
[0006] Furthermore, the multimodal interaction module includes a visual perception unit, a voice perception unit, and other modal perception units; The visual perception unit is equipped with a high-resolution RGB camera and a 3D-ToF sensor to capture the user's facial expressions, body movements and spatial location information in real time. The facial expressions include smiling and frowning, and the body movements include nodding and waving. The visual perception unit can obtain the user's emotional state and intention by recognizing the above expressions and movements. The voice perception unit is equipped with a high-performance microphone array for high-precision acquisition and recognition of user voice, and can use voice recognition algorithms to analyze the tone, speed and volume characteristics of the voice to infer the user's emotional state. The skin sensing unit integrates a skin conductance sensor for non-invasive monitoring of the user's physiological signals. By detecting changes in the user's skin conductance response, it can determine the user's stress level or level of excitement.
[0007] Furthermore, the emotion computing module includes an emotion recognition unit and an emotion response unit; The emotion recognition unit uses data acquired by the multimodal interaction module and deep learning algorithms to construct an emotion recognition model to classify and predict the user's emotional state, which includes happiness, sadness, anxiety, and fatigue. The emotion recognition model can be trained and optimized with new data to improve recognition accuracy. The emotion response unit generates a corresponding emotion response strategy based on the user's emotional state identified by the emotion recognition unit.
[0008] Furthermore, the self-learning module includes a daily behavior learning unit and an interaction strategy optimization unit; The daily behavior learning unit is based on a federated learning framework. It learns the user's daily habits, interests and behavior patterns during the daily interaction between the electronic pet and the user. The daily habits include the user's daily wake-up, sleep and meal times. The interests include the user's favorite music, movies and books. It can also provide personalized services to the user based on the information learned. The interaction strategy optimization unit is based on a reinforcement learning algorithm. It optimizes its own interaction strategy according to the feedback results of the interaction between the electronic pet and the user. If a certain response method receives positive feedback from the user, the probability of using that response method in similar scenarios is increased. If a certain interaction behavior causes user dissatisfaction or no response, the interaction behavior is adjusted.
[0009] Furthermore, the growth and evolution system includes a multi-dimensional growth mechanism unit and a level update and evolution unit; The multi-dimensional growth mechanism unit has multiple interactive dimensions, including a learning dimension, a gaming dimension, a check-in dimension, and a travel dimension. In the learning dimension, the electronic pet can interact with the user based on a target first-category course from multiple first-category courses to help the user learn the course knowledge, or it can count down based on a target second-category course from multiple second-category courses to simulate its own learning process and answer questions from the user based on the learned knowledge. In the gaming dimension, the electronic pet can play games such as riddles and chess with the user. The check-in dimension is used to encourage users to complete check-in tasks according to a preset cycle. In the travel dimension, the electronic pet can interact with the user based on multiple travel destinations to simulate the travel process. After the electronic pet completes the task in each interaction dimension, the level update and evolution unit rewards the electronic pet with a growth representation value of at least one of the multiple target growth dimensions, including intelligence, emotion, and physical strength. When the growth representation values of multiple target growth dimensions meet specific level update conditions and the electronic pet's age is greater than an age threshold, the electronic pet upgrades to the next level. The level update conditions are that the growth representation value of each target growth dimension is greater than the corresponding threshold, or the comprehensive growth representation value obtained by fusing the growth representation values of each target growth dimension is greater than the comprehensive threshold. After the electronic pet upgrades, it can unlock new functions, appearances, and interaction methods.
[0010] Furthermore, the physical form and motion control module includes a life-like motion control unit and a personalized appearance customization unit; The life-like motion control unit draws on embodied intelligence technology. Its joint drive module can achieve a variety of natural postures. The electronic pet's tail structure uses flexible materials and bionic motors, which can convey emotions through wagging. Rapid wagging indicates excitement, while slow curling suggests drowsiness. The personalized appearance customization unit adopts a modular design, and the electronic pet has detachable fur components and shells, allowing users to personalize the appearance of the electronic pet according to their preferences.
[0011] Furthermore, when the visual perception unit detects a user smiling, it can control the electronic pet to exhibit a cheerful posture, move around the user, or make affectionate gestures. When the voice perception unit detects that the user is speaking in an anxious tone, it can control the electronic pet to sense the user's emotions and provide a soothing response. When the emotion recognition unit detects that the user is in a sad state, it can control the electronic pet to play soothing music, offer comfort with a gentle voice, or perform a hugging action; when it detects that the user is in an excited state, it can control the electronic pet to display excited postures and interact more actively with the user.
[0012] Furthermore, the daily behavior learning unit can control the electronic pet to play the user's favorite music and recommend relevant content based on the user's interests when the user wakes up. In the multi-dimensional growth mechanism unit, the multiple first-type courses and multiple second-type courses are course resources pre-stored in the electronic pet storage module, and the course resources can be updated via the network.
[0013] Furthermore, the multimodal interaction module can also integrate temperature and heart rate sensors to supplement the monitoring of the user's physiological state information, including body surface temperature and heart rate changes. The daily behavior learning unit of the self-learning module can periodically organize and update the learned user's lifestyle habits, interests, and behavioral patterns to ensure that the personalized services provided match the user's current needs. After the electronic pet is upgraded, the level update and evolution unit of the growth and evolution system will generate an upgrade log, which records the new functions, appearance and interaction methods unlocked by the electronic pet for users to view.
[0014] Furthermore, the daily behavior learning unit includes a knowledge base of common disease symptoms, prevention methods, and care tips, providing timely diagnostic and prevention suggestions for common diseases. It also features a customized health plan that is tailored to the user's individual characteristics, daily routines, and dietary habits, including exercise arrangements, dietary recommendations, and timely reminders.
[0015] The beneficial effects of this invention are as follows: Through multimodal interaction and affective computing technology, electronic pets can understand users' emotions and intentions more deeply and make more targeted and emotionally resonant responses, thereby significantly enhancing the emotional connection with users and making electronic pets a true emotional companion for users, thus strengthening the emotional connection. The self-learning module enables the electronic pet to provide personalized services and interactions based on the user's behavior and preferences, meeting the diverse needs of different users and creating a unique electronic pet experience for each user, thus enhancing the personalized experience. The multi-dimensional growth mechanism and level update evolution system provide users with rich interactive content and a continuous sense of purpose, increasing the interaction stickiness between users and their electronic pets, allowing users to gain more fun and a sense of accomplishment in raising their electronic pets, and enriching the growth and evolution experience. By combining advanced AI technology, a more natural and intelligent interaction method has been achieved, breaking through the limitations of traditional electronic pet interaction and bringing a new direction for development to the electronic pet field, thus innovating the interaction method.
[0016] The above description is merely an overview of the technical solution of the present invention. In order to better understand the technical means of the present invention and to implement it in accordance with the contents of the specification, the preferred embodiments of the present invention are described in detail below. Detailed Implementation
[0017] The technical solutions of the present invention will now be clearly and completely described. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.
[0018] In the description of this invention, it should be noted that, unless otherwise explicitly specified and limited, the terms "installation," "connection," and "linking" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal connection of two components. Those skilled in the art can understand the specific meaning of the above terms in this invention based on the specific circumstances.
[0019] Furthermore, the technical features involved in the different embodiments of the present invention described below can be combined with each other as long as they do not conflict with each other.
[0020] The preferred embodiment of this application shows an intelligent electronic pet system based on artificial intelligence multimodal interaction and autonomous learning, including a multimodal interaction module, an emotion computing module, an autonomous learning module, a growth and evolution system, and a physical form and motion control module. The multimodal interaction module captures the user's facial expressions, body movements, voice features, and physiological signals in real time to comprehensively perceive the user's state. The emotion computing module uses deep learning models to identify the user's emotional state based on the data acquired by the multimodal interaction module and generates emotional response strategies such as playing music, providing comforting voices, and engaging in affectionate actions. The autonomous learning module learns the user's lifestyle habits and interests using a learning framework and optimizes the interaction strategy by combining reinforcement learning algorithms to provide personalized services. The growth and evolution system sets up multi-dimensional interactive tasks and rewards corresponding growth representation values based on task completion. When the level update conditions are met, the system upgrades and evolves the functions, appearance, and interaction methods. The physical form and motion control module uses embodied intelligence technology to achieve life-like movement, conveys emotions through flexible materials and biomimetic motor design, and supports users to customize personalized appearance through modular components.
[0021] The multimodal interaction module includes a visual perception unit, a voice perception unit, and other modal perception units; The visual perception unit is equipped with a high-resolution RGB camera and a 3D-ToF sensor to capture the user's facial expressions, body movements and spatial location information in real time. Facial expressions include smiling and frowning, and body movements include nodding and waving. The visual perception unit can obtain the user's emotional state and intention by recognizing the above expressions and movements. The voice perception unit is equipped with a high-performance microphone array for high-precision acquisition and recognition of user voice, and can use voice recognition algorithms to analyze the tone, speed and volume characteristics of the voice to infer the user's emotional state. The skin sensing unit integrates a skin conductance sensor for non-invasive monitoring of the user's physiological signals. By detecting changes in the user's skin conductance response, it can determine the user's stress level or level of excitement.
[0022] The emotion computing module includes an emotion recognition unit and an emotion response unit; The emotion recognition unit uses data acquired by the multimodal interaction module and deep learning algorithms to build an emotion recognition model to classify and predict users' emotional states, including happiness, sadness, anxiety, and fatigue. The emotion recognition model can be trained and optimized with new data to improve recognition accuracy. The emotion response unit generates corresponding emotion response strategies based on the user's emotional state identified by the emotion recognition unit.
[0023] The self-learning module includes a daily behavior learning unit and an interaction strategy optimization unit; The daily behavior learning unit is based on the federated learning framework. It learns the user's daily habits, interests and behavior patterns during the daily interaction between the electronic pet and the user. The daily habits include the user's daily wake-up time, sleep time and meal time. The interests include the user's favorite music, movies and books. It can also provide personalized services to the user based on the information learned. The interaction strategy optimization unit is based on reinforcement learning algorithm. It optimizes its own interaction strategy according to the feedback results of the interaction between the electronic pet and the user. If a certain response method receives positive feedback from the user, the probability of using that response method in similar scenarios will be increased. If a certain interaction behavior causes user dissatisfaction or no response, the interaction behavior will be adjusted.
[0024] The growth and evolution system includes multi-dimensional growth mechanism units and level update and evolution units; The multi-dimensional growth mechanism features multiple interactive dimensions, including learning, gaming, check-in, and travel. In the learning dimension, the electronic pet can interact with users based on multiple target courses in the first category to help them learn, or it can simulate its own learning process by counting down to multiple target courses in the second category and answer user questions based on the learned knowledge. In the gaming dimension, the electronic pet can play games such as riddles and chess with users. The check-in dimension encourages users to complete check-in tasks according to a preset cycle. In the travel dimension, the electronic pet can interact with users based on multiple travel destinations to simulate the travel process. After the electronic pet completes the task in each interaction dimension, the level update and evolution unit rewards the electronic pet with a growth representation value of at least one of the multiple target growth dimensions, including intelligence, emotion, and physical strength. When the growth representation values of multiple target growth dimensions meet specific level update conditions, and the electronic pet's age is greater than the age threshold, the electronic pet upgrades to the next level. The level update conditions are that the growth representation value of each target growth dimension is greater than the corresponding threshold, or the comprehensive growth representation value obtained by merging the growth representation values of each target growth dimension is greater than the comprehensive threshold. After the electronic pet upgrades, it can unlock new functions, appearances, and interaction methods.
[0025] The physical form and motion control module includes a life-like motion control unit and a personalized appearance customization unit; The life-like motion control unit draws on embodied intelligence technology. Its joint drive module can achieve a variety of natural postures. The electronic pet's tail structure uses flexible materials and bionic motors, which can convey emotions through wagging. Rapid wagging indicates excitement, while slow curling suggests drowsiness. The personalized appearance customization unit adopts a modular design, with detachable fur components and shells for users to personalize the appearance of their electronic pets according to their preferences.
[0026] When the visual perception unit detects a user smiling, it can control the electronic pet to display cheerful postures, move around the user, or make affectionate gestures. When the voice perception unit recognizes that the user is speaking in an anxious tone, it can control the electronic pet to sense the user's emotions and provide a soothing response. When the emotion recognition unit detects that the user is in a sad state, it can control the electronic pet to play soothing music, offer comfort with a gentle voice, or perform a hug. When it detects that the user is in an excited state, it can control the electronic pet to display excited postures and interact more actively with the user.
[0027] The daily behavior learning unit can control the electronic pet to play the user's favorite music and recommend relevant content based on the user's interests when the user wakes up. In the multi-dimensional growth mechanism unit, multiple Category 1 courses and multiple Category 2 courses are course resources pre-stored in the electronic pet storage module, and the course resources can be updated via the network.
[0028] The multimodal interaction module can also integrate temperature and heart rate sensors to supplement the monitoring of the user's physiological status information, including body surface temperature and heart rate changes. The daily behavior learning unit of the self-learning module can regularly organize and update the user's learned lifestyle habits, interests, and behavioral patterns to ensure that the personalized services provided match the user's current needs. After the electronic pet is upgraded, the level update and evolution unit of the growth and evolution system will generate an upgrade log, which records the new functions, appearance and interaction methods unlocked by the electronic pet for users to view.
[0029] The daily behavior learning unit includes a knowledge base of common disease symptoms, prevention methods, and care tips, providing timely suggestions for the diagnosis and prevention of common diseases. It also features a customized health plan, which is designed based on the user's personal characteristics, daily routines, diet, and other lifestyle habits. The plan includes exercise arrangements, dietary recommendations, and timely reminders.
[0030] In summary, this invention provides an intelligent electronic pet system based on artificial intelligence multimodal interaction and autonomous learning. Through multimodal interaction and affective computing technology, the electronic pet can more deeply understand the user's emotions and intentions, and make more targeted and emotionally resonant responses, thereby significantly enhancing the emotional connection with the user and making the electronic pet a true emotional companion to the user. The self-learning module enables the electronic pet to provide personalized services and interactions based on the user's behavior and preferences, meeting the diverse needs of different users and creating a unique electronic pet experience for each user, thus enhancing the personalized experience. The multi-dimensional growth mechanism and level update evolution system provide users with rich interactive content and a continuous sense of purpose, increasing the interaction stickiness between users and their electronic pets, allowing users to gain more fun and a sense of accomplishment in raising their electronic pets, and enriching the growth and evolution experience. By combining advanced AI technology, a more natural and intelligent interaction method has been achieved, breaking through the limitations of traditional electronic pet interaction and bringing a new direction for development to the electronic pet field, thus innovating the interaction method.
[0031] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.
[0032] The embodiments described above are merely illustrative of implementation methods of the present invention, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of the invention patent. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of the present invention, and these all fall within the protection scope of the present invention. Therefore, the protection scope of this invention patent should be determined by the appended claims.
Claims
1. An intelligent electronic pet system based on artificial intelligence multimodal interaction and autonomous learning, characterized in that: It includes a multimodal interaction module, an affective computing module, an autonomous learning module, a growth and evolution system, and a physical form and motion control module. The multimodal interaction module captures the user's facial expressions, body movements, voice features, and physiological signals in real time to comprehensively perceive the user's state. Based on the data obtained by the multimodal interaction module, the affective computing module uses a deep learning model to identify the user's emotional state and generate emotional response strategies such as playing music, providing comforting voice messages, and engaging in intimate gestures. The self-learning module uses a learning framework to learn users' lifestyle habits and interests, and combines reinforcement learning algorithms to optimize interaction strategies and provide personalized services. The growth and evolution system sets up multi-dimensional interactive tasks and rewards users with corresponding growth performance based on task completion. When the level update conditions are met, the system upgrades and evolves the functions, appearance, and interaction methods. The physical form and motion control module draws on embodied intelligence technology to achieve life-like movement, conveys emotions through flexible materials and biomimetic motor design, and supports users to customize personalized appearance through modular components.
2. The intelligent electronic pet system based on artificial intelligence multimodal interaction and autonomous learning according to claim 1, characterized in that, The multimodal interaction module includes a visual perception unit, a voice perception unit, and other modal perception units; The visual perception unit is equipped with a high-resolution RGB camera and a 3D-ToF sensor to capture the user's facial expressions, body movements and spatial location information in real time. The facial expressions include smiling and frowning, and the body movements include nodding and waving. The visual perception unit can obtain the user's emotional state and intention by recognizing the above expressions and movements. The voice perception unit is equipped with a high-performance microphone array for high-precision acquisition and recognition of user voice, and can use voice recognition algorithms to analyze the tone, speed and volume characteristics of the voice to infer the user's emotional state. The skin sensing unit integrates a skin conductance sensor for non-invasive monitoring of the user's physiological signals. By detecting changes in the user's skin conductance response, it can determine the user's stress level or level of excitement.
3. The intelligent electronic pet system based on artificial intelligence multimodal interaction and autonomous learning as described in claim 2, characterized in that, The emotion computing module includes an emotion recognition unit and an emotion response unit; The emotion recognition unit uses data acquired by the multimodal interaction module and deep learning algorithms to construct an emotion recognition model to classify and predict the user's emotional state, which includes happiness, sadness, anxiety, and fatigue. The emotion recognition model can be trained and optimized with new data to improve recognition accuracy. The emotion response unit generates a corresponding emotion response strategy based on the user's emotional state identified by the emotion recognition unit.
4. The intelligent electronic pet system based on artificial intelligence multimodal interaction and autonomous learning as described in claim 2, characterized in that, The self-learning module includes a daily behavior learning unit and an interaction strategy optimization unit; The daily behavior learning unit is based on a federated learning framework. It learns the user's daily habits, interests and behavior patterns during the daily interaction between the electronic pet and the user. The daily habits include the user's daily wake-up, sleep and meal times. The interests include the user's favorite music, movies and books. It can also provide personalized services to the user based on the information learned. The interaction strategy optimization unit is based on reinforcement learning algorithm and optimizes its own interaction strategy according to the feedback results of the interaction between the electronic pet and the user. If a certain response method receives positive feedback from the user, the probability of using that response method in similar scenarios will be increased. If a certain interaction behavior causes user dissatisfaction or no response, the interaction behavior will be adjusted.
5. The intelligent electronic pet system based on artificial intelligence multimodal interaction and autonomous learning as described in claim 2, characterized in that, The growth and evolution system includes a multi-dimensional growth mechanism unit and a level update and evolution unit; The multi-dimensional growth mechanism unit is equipped with multiple interactive dimensions, including learning, gaming, check-in, and travel dimensions. In the learning dimension, the electronic pet can interact with the user based on a target first-category course from multiple first-category courses to help the user learn course knowledge, or count down based on a target second-category course from multiple second-category courses to simulate its own learning process, and can answer questions from the user based on the learned knowledge; in the game dimension, the electronic pet can play games such as riddles and chess with the user; the check-in dimension is used to encourage the user to perform check-in tasks according to a preset cycle; in the travel dimension, the electronic pet can interact with the user based on multiple travel destinations to simulate the travel process; After the electronic pet completes the task in each interaction dimension, the level update and evolution unit rewards the electronic pet with a growth representation value of at least one of the multiple target growth dimensions, including intelligence, emotion, and physical strength. When the growth representation values of multiple target growth dimensions meet specific level update conditions and the electronic pet's age is greater than an age threshold, the electronic pet upgrades to the next level. The level update conditions are that the growth representation value of each target growth dimension is greater than the corresponding threshold, or the comprehensive growth representation value obtained by fusing the growth representation values of each target growth dimension is greater than the comprehensive threshold. After the electronic pet upgrades, it can unlock new functions, appearances, and interaction methods.
6. The intelligent electronic pet system based on artificial intelligence multimodal interaction and autonomous learning as described in claim 2, characterized in that, The physical form and motion control module includes a life-like motion control unit and a personalized appearance customization unit; The life-like motion control unit draws on embodied intelligence technology. Its joint drive module can achieve a variety of natural postures. The electronic pet's tail structure uses flexible materials and bionic motors, which can convey emotions through wagging. Rapid wagging indicates excitement, while slow curling suggests drowsiness. The personalized appearance customization unit adopts a modular design, and the electronic pet has detachable fur components and shells, allowing users to personalize the appearance of the electronic pet according to their preferences.
7. The intelligent electronic pet system based on artificial intelligence multimodal interaction and autonomous learning according to claim 1, characterized in that, When the visual perception unit detects a user smiling, it can control the electronic pet to display a cheerful posture, move around the user, or make affectionate gestures. When the voice perception unit detects that the user is speaking in an anxious tone, it can control the electronic pet to sense the user's emotions and provide a soothing response. When the emotion recognition unit detects that the user is in a sad state, it can control the electronic pet to play soothing music, offer comfort with a gentle voice, or perform a hugging action; when it detects that the user is in an excited state, it can control the electronic pet to display excited postures and interact more actively with the user.
8. The intelligent electronic pet system based on artificial intelligence multimodal interaction and autonomous learning according to claim 1, characterized in that, The daily behavior learning unit can control the electronic pet to play the user's favorite music and recommend relevant content based on the user's interests when the user wakes up. In the multi-dimensional growth mechanism unit, the multiple first-type courses and multiple second-type courses are course resources pre-stored in the electronic pet storage module, and the course resources can be updated via the network.
9. The intelligent electronic pet system based on artificial intelligence multimodal interaction and autonomous learning according to claim 1, characterized in that, The multimodal interaction module can also integrate temperature and heart rate sensors to supplement the monitoring of the user's physiological state information, including body surface temperature and heart rate changes. The daily behavior learning unit of the self-learning module can periodically organize and update the learned user's lifestyle habits, interests, and behavioral patterns to ensure that the personalized services provided match the user's current needs. The growth and evolution system's level update and evolution unit generates an upgrade log after the electronic pet is upgraded, recording the new functions, appearance, and interaction methods unlocked by the electronic pet for users to view.
10. The intelligent electronic pet system based on artificial intelligence multimodal interaction and autonomous learning according to claim 1, characterized in that, The daily behavior learning unit includes a knowledge base of common disease symptoms, prevention methods, and care tips, providing timely suggestions for the diagnosis and prevention of common diseases. It also features a customized health plan, which is designed based on the user's personal characteristics, daily routines, diet, and other lifestyle habits. The plan includes exercise arrangements, dietary recommendations, and timely reminders.