AMR Task List Exchange for Route Optimization Without Network Coverage
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Modern warehouses face challenges in optimizing the paths and task lists of autonomous mobile robots (AMRs) due to inadequate communication infrastructure, leading to suboptimal performance in 'dock to dock time' and 'pick and pack performance', as AMRs often operate independently without continuous central control and lack the ability to exchange information effectively.
Innovation Solution
Implementing a distributed mechanism that allows AMRs to exchange task lists during serendipitous encounters, enabling them to adjust and optimize their tasks based on comparisons, thereby optimizing their routes and inventory management without relying on continuous network connectivity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If AMRs operate autonomously without continuous central control to improve reliability in environments with inadequate communication infrastructure, then the system's adaptability improves, but the ability to optimize paths and task lists deteriorates
Solution Approach 1:
The patent combines centralized control capabilities with autonomous operation by enabling AMRs to exchange information and coordinate tasks peer-to-peer when disconnected from central control. This merging allows the system to maintain optimization capabilities through distributed collaboration while adapting to environments with inadequate communication infrastructure.
Solution Approach 2:
The system dynamically switches between centralized control mode (when connected) and distributed autonomous mode (when disconnected). This dynamic adaptability allows AMRs to maintain productivity through local optimization while adapting to varying communication conditions in the warehouse environment.
2Productivity
If AMRs exchange task lists during serendipitous encounters to improve productivity through opportunistic optimization, then the loss of time is reduced, but the device complexity increases
Solution Approach 1:
AMRs perform self-optimization by autonomously exchanging task list information with other AMRs during encounters. Each robot independently determines whether to adjust its task list based on received information, eliminating the need for complex centralized coordination while improving productivity through opportunistic task reallocation.
3Ease of operation
If AMRs operate independently without information exchange to reduce device complexity, then the ease of operation improves, but the loss of information about other AMRs' tasks increases
Solution Approach 1:
Task lists serve as intermediaries that carry information about AMR tasks and locations. By exchanging these standardized data structures during encounters, AMRs gain awareness of other robots' activities without requiring complex direct communication protocols, thus reducing information loss while maintaining operational simplicity.
Data Source
AI summary
According to one or more embodiments of the disclosure, a first autonomous mobile robot (AMR) encounters a second AMR, while navigating a location. The first AMR receives, from the second AMR, a task list of the second AMR. The first AMR determines an adjustment to the task list of the second AMR, based in part on a comparison between the task list of the second AMR and a task list maintained by the first AMR. The first AMR sends, to the second AMR, the adjustment to the task list of the second AMR.