Robot Queue Control for Task Assignment and Charging Flow
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Solution Overview
Problem
Existing robot control systems face challenges in efficiently managing multiple robots in a queuing manner, particularly in accurately determining robot positions and integrating their control, which affects task assignment and charging processes, especially when charging docks are insufficient.
Innovation Solution
A robot travel control system and method that uses a server to assign tasks, manage queue positions, and optimize charging processes by calculating occupancy rates and State of Charge (SoC) levels, allowing robots to automatically adjust their positions and move to charging docks based on queue states and task schedules.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If each robot determines its position based on camera recognition, then the system allows autonomous operation, but position accuracy is lowered and integrated control becomes difficult
Solution Approach 1:
The patent introduces a server as an intermediary that receives position information from multiple robots and performs centralized queue management. The server calculates queue positions based on robot coordinates and manages task assignments, acting as a mediator between individual robots and the control system. This resolves the contradiction by maintaining autonomous robot operation while achieving accurate position determination through server-based calculation.
2Extent of automation
If robots individually determine charging needs, then each robot operates independently, but efficient integrated charging becomes difficult when charging docks are insufficient
Solution Approach 1:
The patent merges individual robot charging decisions into a unified server-based charging management system. The server monitors battery levels of all robots, determines charging priorities based on queue positions and task schedules, and coordinates charging dock allocation. This combining approach enables efficient integrated charging by optimizing the use of limited charging docks across the entire robot fleet rather than allowing independent, uncoordinated charging requests.
3Device complexity
If multiple robots operate without integrated queue management, then system complexity is reduced, but task assignment speed and accuracy decrease
Solution Approach 1:
The patent segments the control system into two distinct layers: individual robot control units that handle autonomous navigation and basic operations, and a centralized server that handles queue management and task assignment. This segmentation allows robots to operate independently with simple control logic while the server provides coordinated task assignment and queue management. The division resolves the contradiction by keeping individual robot complexity low while achieving high task assignment efficiency through centralized intelligence.
Data Source
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AI summary
A method performed by a server(100) configured to communicate with a plurality of robots(200), can include forming(310) a queue of the plurality of robots, assigning(320) a task to at least one of the plurality of robots within the queue, releasing(330) a queue mode of the task-assigned robot when the task-assigned robot departs from a queue of the plurality of robots, and shifting(340) at least one or more robots among the plurality of robots within the queue forward by checking an occupancy rate for a forward part of the queue, in response to the departure of the task-assigned robot from the queue.