Mobile Robot Allocation Using Task Status Feedback
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Solution Overview
Problem
Existing mobile robot allocation systems lack efficiency in optimizing the allocation of multiple mobile robots across various areas based on task status, leading to suboptimal resource utilization and potential delays in production processes.
Innovation Solution
A mobile robot allocation system comprising an obtainer, allocator, and outputter that obtains task status information, allocates mobile robots to areas based on task requirements, and outputs allocation information, ensuring that the number of robots is proportional to the task demands and considering their roles, thereby optimizing resource allocation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If mobile robots are allocated to areas based on manual or simple methods, then the allocation process is simple to implement, but the resource utilization is suboptimal and production efficiency is reduced
Solution Approach 1:
The allocation system continuously receives task status information from areas, processes this feedback data, and dynamically adjusts robot allocations based on current workload conditions. This closed-loop feedback mechanism enables optimized resource utilization while maintaining manageable system complexity through automated decision-making.
Solution Approach 2:
The system automatically performs allocation optimization without requiring manual intervention. The allocation unit autonomously processes task status information and generates optimized allocation plans, allowing the system to self-manage resource distribution and improve productivity independently.
2Reliability
If the number of mobile robots in each area is increased to meet task demands, then task completion capability is improved, but resource utilization becomes inefficient when task demand is low
Solution Approach 1:
The robot allocation is made dynamic rather than static. The allocation unit continuously adjusts the number and distribution of robots across areas based on real-time task status information, ensuring that robot deployment matches actual task demands. This dynamic adjustment prevents both over-allocation and under-allocation, optimizing resource utilization while maintaining task completion capability.
3Productivity
If mobile robots are allocated without considering task status information, then the allocation process is faster and simpler, but resource allocation becomes suboptimal and delays occur
Solution Approach 1:
The system performs preliminary processing of task status information and maintains ready-to-execute allocation plans. By continuously monitoring area conditions and pre-computing allocation strategies, the system minimizes decision-making time when allocation adjustments are needed, thus improving resource allocation efficiency without significant time loss.
Data Source
AI summary
A mobile robot allocation system includes an obtainer, an allocator, and an outputter. The obtainer obtains task status information regarding a task status of each of a plurality of areas, the plurality of areas each including a plurality of machines. The allocator allocates, based on the task status information obtained by the obtainer, a plurality of mobile robots to the plurality of areas, the plurality of mobile robots each moving and performing a task in an area among the plurality of areas. The outputter outputs allocation information indicating allocation of the plurality of mobile robots performed by the allocator.