Robot Dispatch Control Using User-State Priority and Task Matching
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Solution Overview
Problem
Existing robot control systems fail to effectively match task-specific user requirements with available robot capabilities, leading to inefficiencies in robot dispatch and increased waiting times for users with urgent requests.
Innovation Solution
A robot control system that includes a receiving unit for dispatch requests, a sensor to detect user states, and a controller that determines priority based on user tasks and psychological states, using a robot use probability conversion table to select the most suitable robot for dispatch, and directs the robot's route to optimize delivery.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If robots are dispatched in order of receiving requests, then the system maintains simple dispatch logic, but users with urgent requests experience increased waiting times
Solution Approach 1:
The system performs preliminary detection of user state (via sensors) and preliminary specification of task type before robot dispatch decision is made. This allows the system to pre-determine priority levels and select appropriate robots in advance, reducing actual waiting time while maintaining manageable complexity through automated preliminary assessments
Solution Approach 2:
The dispatch system dynamically adjusts priority based on real-time user state detection and task specification. The controller can change dispatch order dynamically according to user needs and robot availability, rather than following a fixed queue, thereby reducing waiting time for urgent requests without requiring complex manual intervention
2Reliability
If the system detects user state and specifies task to determine priority, then robot dispatch accuracy improves, but the system complexity increases
Solution Approach 1:
The system uses sensors to automatically detect user state and specifies task type without manual input. The controller autonomously determines priority and selects appropriate robots based on detected information, eliminating the need for complex user interfaces or manual dispatch decisions while improving accuracy through objective sensor-based assessment
Solution Approach 2:
The controller acts as an intermediary that processes sensor data about user state and translates it into appropriate robot dispatch decisions. This intermediary layer simplifies the overall system by centralizing the complex decision-making logic in one component rather than distributing complexity across multiple subsystems
3Reliability
If a robot use probability conversion table is used to select appropriate robots, then task-robot matching accuracy improves, but information processing complexity increases
Solution Approach 1:
The robot use probability conversion table is prepared in advance, storing pre-calculated matching probabilities between different task types and robot capabilities. This preliminary organization of data allows the controller to quickly retrieve appropriate robot selections without performing complex real-time analysis, improving matching accuracy while minimizing processing complexity
Solution Approach 2:
The system uses a conversion table that transforms task specifications into probability values representing suitable robot selections. By changing the parameter representation from direct robot selection to probability-based scoring, the system achieves more accurate matching while keeping the data structure simple and easily updatable
Data Source
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AI summary
A robot control system includes: plural robots; a receiving unit that receives a robot dispatch request from a user; a sensor that detects a state of the user who performs the robot dispatch request; and a controller that determines priority on the robot dispatch request based on the state of the user detected by the sensor, selects, in a case where plural robot dispatch requests are received, a robot to be dispatched among the plural robots in order of the priority on the robot dispatch requests, and dispatches the robot.