Patrolling Robot Route Control Using Demand and Support Sensing
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Solution Overview
Problem
Existing serving robots are not suitable for distributing or retrieving serving objects while patrolling around event venues, such as cocktail parties or conferences, and lack the ability to determine tasks and travel routes based on demand and location information.
Innovation Solution
A method for controlling a patrolling robot that acquires weight and image information from its supports and location data to determine tasks and travel routes, estimating demand for serving objects in each space and adjusting its actions accordingly.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If conventional serving robots are used for taking orders and transporting food in restaurants, then they can perform serving tasks according to orders, but they are not suitable for distributing or retrieving serving objects while patrolling around event venues
Solution Approach 1:
The robot transitions from static order-taking mode to dynamic patrolling mode. The control unit dynamically adjusts the robot's behavior based on real-time situation information, enabling it to patrol event venues while distributing and retrieving serving objects, thus adapting to different service scenarios
Solution Approach 2:
The robot is designed to perform multiple functions: it can take orders in restaurants, patrol event venues, distribute serving objects, and retrieve used items. The support structure with weight sensors and image recognition capabilities enables universal application across different service environments
2Productivity
If the robot patrols around event venues to distribute serving objects, then it can serve attendees, but it lacks the ability to determine tasks and travel routes based on demand and location information
Solution Approach 1:
The robot uses weight information from the support to detect when serving objects are placed or removed, and image recognition to identify locations and attendees. This feedback mechanism enables the control unit to determine appropriate tasks and travel routes based on real-time situation information, improving service efficiency
Solution Approach 2:
The robot acquires situation information including weight data and image information before determining tasks. By processing demand and location information in advance, the robot can plan its travel route and service actions proactively rather than reactively
3Adaptability or versatility
If the robot uses weight information and image information to determine tasks and routes, then it can optimize resource allocation, but it requires complex information processing capabilities
Solution Approach 1:
The information processing system is segmented into distinct functional modules: weight sensors in the support for detecting serving object changes, image recognition units for location and attendee identification, and a control unit for integrating this data. This modular approach enables complex decision-making while managing system complexity through functional separation
Data Source
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AI summary
A method for controlling a patrolling robot is provided. The method includes the steps of: acquiring, as first situation information on the patrolling robot, at least one of weight information on a support coupled to the patrolling robot and image information on the support and information on a location of the patrolling robot in a patrolling place; and determining a task and a travel route of the patrolling robot on the basis of the first situation information.