Mobile Robot Unmanned Payment System
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Solution Overview
Problem
Current unmanned mobile robots in retail environments are limited to only transferring food and require separate devices or human intervention for payment processing, lacking the capability for automated product recognition and payment processing.
Innovation Solution
An unmanned payment method and system using a mobile robot equipped with camera sensors, weight sensors, and proximity sensors to recognize selected products, determine the corresponding table, and process payments automatically, reducing human labor and enhancing convenience.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If a mobile robot is used for food delivery, then service quality and labor reduction are improved, but the robot lacks payment processing capability requiring separate devices
Solution Approach 1:
The patent combines multiple functions (food delivery, product recognition, table identification, and payment processing) into a single mobile robot system. The robot integrates camera sensors for product recognition, proximity sensors for table identification, and communication modules for payment processing, eliminating the need for separate payment devices and achieving full automation.
Solution Approach 2:
The mobile robot is designed as a multi-functional device that can perform food delivery, recognize products taken by customers, identify their tables using proximity sensors, and process payments all through one unified system. This universal design allows the robot to handle complete service cycles from delivery to payment without requiring additional specialized devices.
2Ease of operation
If separate devices are used for payment processing, then the mobile robot maintains simple function, but labor cost and operational complexity increase
Solution Approach 1:
By merging payment processing capabilities directly into the mobile robot, the system eliminates the need for customers to interact with separate payment devices or wait for staff intervention. The robot autonomously completes the entire service cycle including delivery, product recognition, table identification, and payment processing, thereby improving service efficiency while maintaining operational simplicity.
3Loss of time
If manual payment processing is used, then device complexity is reduced, but human labor requirements and operational time increase
Solution Approach 1:
The mobile robot system enables self-service payment processing where the robot autonomously recognizes products taken by customers, identifies their tables using proximity sensors, calculates payment amounts, and processes payments without any human intervention. This self-service capability eliminates manual payment processing time and achieves complete automation in the payment workflow.
Solution Approach 2:
The system performs preliminary actions by having the robot continuously monitor and recognize products on the delivery platform before customers take them, and by pre-identifying customer tables using proximity sensors. This preliminary data collection enables rapid automated payment processing without requiring manual intervention during the actual payment moment.
4Measurement precision
If the robot recognizes products using only image data, then system complexity is minimized, but recognition accuracy decreases
Solution Approach 1:
The patent merges multiple sensing modalities including camera sensors for visual product recognition and proximity sensors for spatial context and table identification. By combining these different sensor types, the system achieves higher product recognition accuracy and more reliable table identification compared to using image data alone, while maintaining manageable system complexity through integrated processing.
Data Source
AI summary
Disclosed herein are an unmanned payment method and system using a mobile robot in a store. The unmanned payment method includes: acquiring an image through a camera sensor installed above the plate of a mobile robot; recognizing a product, selected and taken by a customer, using the acquired image; identifying a table related to the customer; and calculating a payment amount for the product for the identified table.