Robot Controller Natural Language Processing History Log
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Solution Overview
Problem
Existing robot controllers cannot efficiently process user instructions in natural language, limiting the robot's ability to work flexibly and perform intended actions.
Innovation Solution
A controller that includes an input unit, output unit, input buffer, processing unit, and history log storage unit, which receives user instructions, transmits prompts to a natural language processing system, and generates action commands for the robot based on responses, considering the history of interactions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a robot controller processes user instructions in natural language, then the robot's flexibility and ability to perform intended actions is improved, but the processing efficiency and response time deteriorates
Solution Approach 1:
The system performs preliminary actions by pre-processing user instructions into structured data formats before natural language processing. The input buffer pre-stores instruction data, and the system prepares prompts with historical context in advance, reducing processing time during actual interaction.
Solution Approach 2:
The controller is segmented into distinct functional modules: input unit for receiving instructions, input buffer for data storage, processing unit for NLP operations, and output unit for responses. This segmentation allows parallel processing and optimizes each component's performance independently.
2Reliability
If the robot considers the history of interactions to work successively, then the accuracy of performing intended actions is improved, but the complexity of the control system increases
Solution Approach 1:
A history log storage unit acts as an intermediary between the input buffer and processing unit. It stores and manages interaction history data, providing contextual information to the processing unit without requiring complex direct connections between all system components.
Solution Approach 2:
The system implements feedback mechanisms where the output unit's responses are fed back into the history log, which then informs subsequent processing. This creates a closed-loop system that improves action accuracy through contextual awareness while maintaining manageable complexity through structured feedback paths.
3Ease of operation
If the controller uses a natural language processing system with a large language model, then the robot's ability to understand user instructions is improved, but the time and computational resources required increase
Solution Approach 1:
The system performs preliminary processing by converting natural language instructions into structured data formats and storing them in the input buffer before NLP processing. Prompts are pre-formatted with historical context, reducing the computational burden during actual language model inference.
Solution Approach 2:
The system extracts only the essential and relevant features from user instructions and historical context that are necessary for the language model processing. This extraction reduces the amount of data requiring intensive computational processing while maintaining understanding accuracy.
Data Source
AI summary
A controller includes an input unit, an output unit, an input buffer, a processing unit, and a history log storage unit. The input unit receives from the user, an instruction for a robot. The output unit configured to output, to the user, a reaction from the robot to the instruction. The input buffer saves data of the instruction. The processing unit transmits a prompt to a natural language processing system, receives a response from the natural language processing system, generates an action command for the robot based on the response, and overwrites the data in the input buffer with an action performed by the robot. The history log storage unit stores a history log in which the data read from the input buffer and the response to the data is accumulated. The processing unit generates the prompt including the data read from the input buffer and the history log.