Care Robot Prompt Control for Customized Service at Lower AI Cost
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Solution Overview
Problem
Conventional care robots struggle to collect and process various types of user-related information effectively, leading to challenges in providing customized services and increasing costs due to frequent use of advanced language models.
Innovation Solution
A care robot equipped with sensors, memory, and processors to acquire and analyze user information, generate prompts for a language model, and determine care services, controlling the timing of input to suppress cost increases.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If advanced algorithms and machine learning models are incorporated into the robot system to enable dynamic decision-making and real-time adaptation, then the robot's ability to provide customized care services is improved, but the design and manufacturing costs increase
Solution Approach 1:
The patent introduces a language model as an intermediary component that processes user information and generates care service decisions. This separates the complex AI processing from the robot's core control system, allowing the robot to leverage external computational power without increasing its own manufacturing complexity. The language model acts as a mediator between raw sensor data and care service execution.
Solution Approach 2:
The patent extracts the complex decision-making functionality from the robot system itself and places it in an external language model service. By taking out the heavy computational burden of advanced algorithms from the physical robot, the system achieves high adaptability without proportionally increasing manufacturing costs, as the computational resources can be shared across multiple robots.
2Measurement precision
If the robot frequently uses the language model to process user information, then the accuracy of determining user needs is improved, but the operational costs increase
Solution Approach 1:
The patent implements periodic action by controlling the robot to input collected information into the language model at specific intervals rather than continuously. This allows the system to maintain accurate user need determination while reducing the frequency of expensive language model invocations, thereby lowering operational costs.
Solution Approach 2:
The patent applies partial action by selectively processing only certain types of information through the language model rather than analyzing all collected data continuously. The robot determines which information requires language model processing based on predefined criteria, achieving sufficient accuracy without the excessive cost of processing every data point through the expensive language model.
3Loss of information
If the robot collects comprehensive user information including activities, environmental conditions, and emotional states, then the quality of prompts for the language model is improved, but the device complexity increases
Solution Approach 1:
The patent applies universality by using a single integrated sensor system that collects multiple types of information (user activities, environmental conditions, emotional states) through unified data processing. Rather than implementing separate specialized systems for each information type, the robot uses multi-functional sensors and a centralized processing approach that reduces overall system complexity while maintaining comprehensive data collection.
Solution Approach 2:
The patent merges multiple information collection functions into a unified processing pipeline. By combining the collection and initial processing of diverse user information into a single integrated system that feeds into prompt generation, the patent reduces complexity compared to having separate independent systems for each information type.
Data Source
AI summary
A care robot according to an embodiment of the present disclosure includes: at least one sensor; a memory configured to store instructions; and a processor operably connected to the memory and configured to execute the instructions. The processor is configured to: acquire robot-collected information related to a user by using the sensor; generate a prompt based on the robot-collected information and transmit the generated prompt to a language model; determine a care service to be provided to the user based on an output received from the language model; and control components of the care robot to perform the determined care service.