Robot Behavior Control Using Emotion History and User State
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Solution Overview
Problem
Existing action control systems fail to effectively adapt to user emotions and interactions, leading to suboptimal responses and a lack of personalization in robot-user interactions.
Innovation Solution
An action control system that includes a user state recognition unit, emotion determination unit, and action determination unit to analyze user and robot emotions, using historical data to determine appropriate actions and gestures based on emotion combinations and individuality settings.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If traditional action control systems are used, then the system structure is simple, but the system cannot effectively adapt to user emotions and interactions
Solution Approach 1:
The system segments the action determination process into multiple independent modules: user state recognition unit, emotion determination unit, action determination unit, and reaction recognition unit. Each module handles a specific aspect of emotion-aware action control, allowing the system to adapt to user emotions without creating a monolithic complex structure.
Solution Approach 2:
The system performs preliminary emotion determination and historical data analysis before executing actions. The emotion determination unit continuously monitors and stores emotion values in historical data, preparing the system to adaptively respond to user emotions in real-time without requiring complex restructuring during action execution.
2Productivity
If emotion-based action determination is implemented, then user engagement improves, but processing requirements increase
Solution Approach 1:
The system uses partial action by selecting and executing only the most relevant actions based on current emotion states and historical patterns, rather than processing all possible actions. The action determination unit filters through multiple emotion values and historical data points to determine the most appropriate action, reducing unnecessary processing energy consumption while maintaining high user engagement.
3Adaptability or versatility
If historical emotion data is stored and analyzed, then action personalization improves, but data storage requirements increase
Solution Approach 1:
The system extracts only the essential emotion values and action patterns from historical data that are most relevant for personalizing actions. The emotion determination unit selectively stores and retrieves specific emotion states and corresponding actions, rather than maintaining complete raw data, thereby achieving effective action personalization with reduced data storage requirements.
Data Source
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AI summary
The action control system includes: a user state recognition unit that recognizes a user state including an action of a user; an emotion determination unit that determines an emotion value indicating an emotion of the user based on the user state; and an action determination unit that determines an action corresponding to the action of the user based on a current emotion value determined by the emotion determination unit and historical data of a past emotion value determined by the emotion determination unit before the current emotion value is determined.