Enhanced State Graphs for Natural Language Machine Control
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Solution Overview
Problem
Existing systems require unnatural command formats for users to interact with machines, making it difficult for humans to achieve their goals effectively.
Innovation Solution
A system that allows users to provide natural language inputs, processes sensor data to identify objects and goals, and generates instructions for mechanical systems to achieve those goals.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If natural language input is used for user-machine interaction, then ease of operation is improved, but device complexity increases due to the need for enhanced state graph processing and natural language interpretation systems
Solution Approach 1:
The patent introduces an enhanced state graph as an intermediary data structure that bridges natural language input and machine execution. The state graph includes natural language text, parsed semantic elements, and executable instructions, serving as a mediator that translates user intent into machine actions without requiring users to learn complex command syntax
Solution Approach 2:
The patent replaces traditional mechanical command-line interfaces and syntax-parsing systems with a natural language processing approach. Instead of requiring users to follow strict grammatical rules or command structures, the system uses semantic parsing of natural language to generate executable instructions, substituting rigid mechanical interaction patterns with flexible language-based communication
2Device complexity
If traditional command formats are used for machine interaction, then device complexity is reduced, but ease of operation deteriorates as users must learn unnatural syntax and grammar
Solution Approach 1:
The enhanced state graph serves multiple functions simultaneously: it stores the original natural language text for reference, contains parsed semantic elements for logic processing, and generates executable instructions for machine execution. This multi-functional data structure eliminates the need for separate processing systems for each function, reducing overall device complexity while maintaining natural language interaction benefits
3Ease of operation
If natural language processing and enhanced state graph generation are implemented, then ease of operation is improved, but loss of information increases during the transformation from natural language to executable instructions
Solution Approach 1:
The enhanced state graph employs a nested structure where the original natural language text is embedded within the graph, and parsed semantic elements are nested within the text. This nested organization preserves all original information at each level while adding processed representations, ensuring no information is lost during transformation from natural language to executable instructions
Data Source
AI summary
A method is provided. The method includes obtaining a state graph that represents a set of objects within an environment and a set of positions of the set of objects within the environment. The state graph includes a set of object nodes and a set of property nodes. The method also includes obtaining user input data. The user input data is generated based on a natural language input. The method further includes updating the state graph based on the user input data to generate an enhanced state graph. The enhanced state graph includes additional nodes generated based on the user input data. The method further includes providing the enhanced state graph to a planning module. The planning modules generates instructions for operating a mechanical system based on the enhanced state graph.