Multi-Robot Route Control for Shared Kitchen Loading Stations
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Solution Overview
Problem
Existing technologies are not suitable for automating transport processes in shared kitchens, as they are primarily designed for traditional restaurant settings.
Innovation Solution
A method and system for controlling a robot that determines a target robot to travel to a loading station based on the location of the station and the task situation of each robot, and determines a travel route that includes both the loading and unloading stations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If conventional robot serving systems are used in shared kitchens, then robot structure and control can be standardized, but the system cannot adapt to the different operational requirements of shared kitchens versus traditional restaurants
Solution Approach 1:
The robot system is designed with multi-functional capabilities to serve both traditional restaurant environments and shared kitchen operations. The robot can perform diverse tasks including transporting food from loading stations to unloading stations, navigating autonomously in different spatial layouts, and interfacing with various station configurations. This universal design allows a single robot architecture to adapt to multiple operational contexts without requiring complete redesign.
2Productivity
If multiple robots are deployed in shared kitchens, then transport capacity increases, but coordination and route determination complexity increases
Solution Approach 1:
The system implements centralized control with real-time feedback mechanisms where the control server continuously monitors the positions, tasks, and statuses of all robots. Based on this feedback, the server dynamically determines optimal route assignments and coordination strategies, allowing multiple robots to operate efficiently without collisions or redundant movements. The feedback loop enables adaptive coordination that scales with the number of robots deployed.
Solution Approach 2:
The control server performs preliminary route determination and task assignment before robots begin their operations. By pre-calculating optimal routes and assigning tasks in advance based on current system state, the server reduces real-time coordination complexity and enables robots to execute predetermined sequences efficiently.
Data Source
AI summary
A method for controlling a robot is provided. The method includes the steps of: determining a target robot to travel to a first loading station among a plurality of robots, on the basis of information on a location of the first loading station and a task situation of each of the plurality of robots, when a first transport target object is placed at the first loading station; and determining a travel route of the target robot with reference to information on the location of the first loading station and a location of a first unloading station associated with the first transport target object.