Guide Robot Control Using User Dynamic Data for Flexible Guidance
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Solution Overview
Problem
Users guided by conventional guidance systems may feel their movement is restricted, leading to stress due to the rigid control of the robot.
Innovation Solution
A guide robot control device that recognizes user dynamic data, estimates guidance requests, and determines guidance actions based on both expressed and potential user needs, including adjusting speed, route, and robot type, to provide a more personalized and stress-reduced experience.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the robot strictly controls the user's movement to ensure accurate guidance, then the guidance accuracy is improved, but the user feels restricted and stressed
Solution Approach 1:
The robot dynamically adjusts its guidance style based on real-time detection of user state (walking speed, direction, stress levels). When the user is moving slowly or showing signs of stress, the robot adapts by providing more flexible guidance options rather than strict control, thereby maintaining accuracy while improving user comfort and freedom.
Solution Approach 2:
The system continuously monitors user dynamic data (movement speed, direction, physiological signals) and uses this feedback to adjust its guidance behavior. This closed-loop control allows the robot to balance guidance precision with user comfort by responding to real-time user state changes.
2Adaptability or versatility
If the robot monitors detailed user dynamic data to personalize guidance, then the guidance suitability is improved, but the system complexity increases
Solution Approach 1:
The robot uses a multi-functional detection system that collects various types of user data (movement, physiology, environment) through integrated sensors. This universal detection approach allows the system to personalize guidance across multiple dimensions without requiring separate specialized systems for each type of monitoring.
Solution Approach 2:
The system automatically processes and analyzes user dynamic data using onboard computing resources, generating personalized guidance plans without requiring external intervention. The robot self-adjusts its behavior based on detected user state, reducing the need for complex external control systems.
3Object-affected harmful factors
If the robot adjusts guidance actions in real-time based on user needs, then the user stress is reduced, but the control complexity increases
Solution Approach 1:
The robot pre-prepares multiple guidance action options based on predicted user needs and potential scenarios. By having predetermined response strategies ready, the robot can quickly adjust to reduce user stress without requiring complex real-time decision-making algorithms, thus lowering control complexity while maintaining effectiveness.
Data Source
AI summary
A server 3 includes a user dynamic data recognition unit 3a1 that recognizes, during guidance, user dynamic data; a guidance request estimation unit 3c that estimates a guidance request of a user during the guidance, based on the user dynamic data; and a guidance action determination unit 3f that determines a guidance action to be taken by a robot 2 during the guidance, based on the estimated guidance request.