Autonomously Motile Device Command Processing
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Solution Overview
Problem
Autonomously motile devices face challenges in processing and responding to unknown voice commands, as they often lack the capability to recognize and execute commands that fall outside their predefined set of known instructions, leading to inefficiencies in user interaction and device operation.
Innovation Solution
The device employs a command processing system that determines if an input command is unknown, prompts the user to define it, and creates a command template by associating generic categories with specific entities, allowing it to execute similar commands in the future, using natural-language understanding and machine learning models to process audio and image data for effective command recognition and execution.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If the device uses a predefined set of known commands, then the device operation is simple and reliable, but the device cannot recognize and execute unknown commands
Solution Approach 1:
The device enables users to define their own custom commands through a simplified interface. The system automatically learns and stores these user-defined commands, allowing the device to serve the user's specific needs without requiring complex pre-programming. This self-service approach expands command versatility while keeping the user interaction simple.
Solution Approach 2:
The command set of the device is made dynamic and adaptable rather than static. The system continuously learns from user interactions and automatically updates its command database. This dynamic nature allows the device to adapt to new commands and usage patterns over time, resolving the contradiction between simplicity and versatility.
2Adaptability or versatility
If the device processes and stores all user commands, then the command versatility increases, but the device complexity and processing requirements increase
Solution Approach 1:
The system extracts and stores only the essential command patterns and intent information, rather than storing complete command histories or complex processing logic. By taking out only the necessary command definitions and their associated parameters, the system achieves high versatility while minimizing storage and processing complexity.
Solution Approach 2:
The command processing system is segmented into distinct functional modules: command detection, intent recognition, parameter extraction, and execution. This segmentation allows each module to handle specific tasks independently, reducing overall system complexity while enabling comprehensive command processing capabilities.
3Reliability
If the device executes commands immediately, then the responsiveness is high, but the reliability decreases when commands are unknown
Solution Approach 1:
The system performs preliminary validation and classification of commands before execution. By pre-checking whether a command is recognized and understanding its intent structure in advance, the system can quickly determine if immediate execution is safe and appropriate. This preliminary action ensures reliability while minimizing delays through efficient pre-processing.
Data Source
AI summary
A device capable of autonomous motion may move in an environment and may receive audio data from a microphone. If the device receives a command represented in the audio data that is absent from a set of known commands, the device may prompt the user to explain how to perform the command. The device may save a command template corresponding to the command, which may be used to perform future commands.