Humanoid Robot Multimodal Dialogue System
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Solution Overview
Problem
Current humanoid robots have limited and predetermined conversational abilities, failing to provide rich and realistic interactions with humans, which is essential for developing companion robots that can assist the elderly, sick, or lonely individuals.
Innovation Solution
A method and system for a humanoid robot that includes a processor, sensor assembly, speech synthesis module, and actuators to perform multimodal dialogue by interpreting user actions, combining verbal and non-verbal inputs to generate responsive gestures and speech, with a dialogue engine that associates input events to output responses, and servo-control for maintaining a natural distance and orientation during interaction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If humanoid robots use predetermined and limited dialogue elements, then the device complexity is reduced and ease of manufacture is improved, but the conversational ability and realism of interaction deteriorate
Solution Approach 1:
The dialogue system is segmented into distinct functional modules: a recognition module that identifies input events (speech, gestures, facial expressions), a rule application module that processes these events against predefined rules, and an output module that generates appropriate responses. This modular architecture allows the robot to achieve versatile conversational abilities while managing system complexity through organized functional decomposition.
Solution Approach 2:
The rule application module serves multiple functions by processing various types of input events (speech recognition results, gesture detections, facial expression analyses) through a unified rule-based framework. This universal processing mechanism allows the same core module to handle diverse interaction modalities, improving adaptability without proportionally increasing complexity.
2Adaptability or versatility
If humanoid robots interpret only verbal inputs, then the device complexity is reduced, but the richness and realism of human-robot interaction deteriorates
Solution Approach 1:
The system merges multiple input modalities (speech recognition, gesture recognition, facial expression analysis) into a unified event recognition framework. The recognition module integrates results from different sensor types and processing algorithms to generate comprehensive input events, enabling rich multi-modal interaction while managing complexity through unified processing architecture.
Solution Approach 2:
The recognition module acts as an intermediary layer between diverse sensors (microphones, cameras, movement sensors) and the rule application module. It translates raw sensor data from multiple modalities into standardized input events that the rule-based system can process, enabling rich multi-modal interaction without overwhelming the core processing architecture.
3Adaptability or versatility
If humanoid robots generate only predetermined responses, then the ease of operation is improved, but the naturalness and expressiveness of dialogue deteriorates
Solution Approach 1:
The rule application module dynamically selects and applies appropriate rules based on the current input events and dialogue context. Rather than using fixed predetermined responses, the system adapts its response generation in real-time by evaluating which rules are most appropriate for the current situation, enabling natural and expressive dialogue while maintaining manageable complexity through context-dependent rule selection.
4Adaptability or versatility
If humanoid robots lack interpretation of non-verbal user actions, then the device complexity is reduced, but the ability to understand user intent and provide realistic interaction deteriorates
Solution Approach 1:
The system applies specialized recognition algorithms tailored to each type of non-verbal cue (gesture recognition for hand movements, facial expression analysis for emotional states). Each sensor type and action category receives dedicated processing optimized for its specific characteristics, enabling accurate user intent understanding from diverse non-verbal actions while managing overall complexity through localized specialized modules.
Data Source
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AI summary
A method of performing a dialogue between a humanoid robot (R) and at least one user (U) comprising the following steps, carried out iteratively by said humanoid robot: i) acquiring a plurality of input signals (s1, s2) from respective sensors (c1, c2), at least one said sensor being a sound sensor and at least one other sensor being a motion or image sensor; ii) interpreting the acquired signals to recognize a plurality of events (EVI) generated by said user, selected from a group comprising: the utterance of at least a word or sentence, an intonation of voice, a gesture, a body posture, a facial expression ; iii) determining a response of said humanoid robot, comprising at least one event (EVO) selected from a group comprising: the utterance of at least a word or sentence, an intonation of voice, a gesture, a body posture, a facial expression; iv) generating, by said humanoid robot, said or each said event; characterized in that said step iii) comprises determining said response as a function of at least two events jointly generated by said user and recognized at said step ii), of which at least one is not a word or sentence uttered by said user. A computer program product and a humanoid robot for carrying out such a method.