Robot Control Using Salient Features for Social Interaction
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Solution Overview
Problem
Existing social robot interaction techniques often fail to consider high-order mechanisms such as internal states and mental states, leading to insufficient responsiveness and life-like operations.
Innovation Solution
A control device and method that integrates knowledge data to monitor and identify salient features in the robot's operation environment, using a hierarchical attention mechanism to quickly adapt operations based on relevance and constraint conditions, updating element information, and adding estimated information to enhance responsiveness.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a stimulus-response pair approach is used for robot operations, then the robot can respond to external stimuli, but the response is insufficient for complex social interactions involving internal states and mental states
Solution Approach 1:
The patent segments the robot's operational framework into multiple hierarchical levels: basic stimulus-response pairs, attention mechanisms for selecting relevant stimuli, and high-order mechanisms for internal states and mental states. This segmentation allows each level to handle specific aspects of social interaction independently while contributing to overall adaptability.
Solution Approach 2:
The patent implements a nested structure where stimulus-response pairs are embedded within attention mechanisms, which are in turn embedded within high-order mechanisms. This nested architecture allows complex social interaction capabilities to be built by layering multiple levels of processing, where each level operates on the output of the previous level.
2Speed
If an attention mechanism is added to detect salient signals, then the robot can quickly respond to important stimuli, but the system complexity increases
Solution Approach 1:
The patent implements preliminary action by pre-defining attention mechanisms and salient feature detection rules before social interactions occur. The system prepares attention weights, detection thresholds, and response protocols in advance, allowing the robot to quickly respond to salient stimuli without performing complex real-time analysis during actual interactions.
Solution Approach 2:
The patent uses copying by creating simplified representations of complex social interaction patterns. Attention mechanisms copy and process only the most salient features of stimuli rather than analyzing all input data in full detail, reducing computational complexity while maintaining response speed for important events.
3Measurement precision
If knowledge data integrating multiple element information is monitored, then the robot can comprehensively understand the operation environment, but the data processing load increases
Solution Approach 1:
The patent extracts and monitors only the most relevant element information from the comprehensive knowledge data based on attention weights and salience criteria. Rather than processing all available data equally, the system selectively extracts and processes only those elements that are currently most relevant to the robot's social interaction context, reducing energy consumption while maintaining perception accuracy.
Data Source
AI summary
A control unit is configured to monitor knowledge data in which element information relating to an operation environment of a robot is integrated and, when the element information of a predetermined item changes, identify a salient feature relating to the element information of the item, and operate the robot on the basis of an operation plan relating to a salient feature identified from related data representing at least a relevance between the salient feature and the operation plan of the robot.