Warehouse Robot Task Allocation Using Multi-Position Search
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Solution Overview
Problem
Existing automated storage and retrieval systems face challenges in optimally allocating jobs and targets to robots due to the separation of job assignment and routing functions, leading to inaccurate time estimates and suboptimal system performance.
Innovation Solution
A system and method that integrates an assigner and a router within a central computer system, utilizing a multi-position search algorithm to allocate jobs and targets to robots based on penalty scores that consider distance, route complexity, and traffic wait times, ensuring efficient robot allocation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If job assignment and routing functions are separated, then system modularity is improved, but allocation accuracy and system performance deteriorate
Solution Approach 1:
The patent merges the previously separated job assignment function and routing function into a unified allocation system. The router now handles both job assignment and route planning simultaneously, allowing it to consider multiple factors (distance, traffic, robot capabilities) when making allocation decisions, thereby improving allocation accuracy while maintaining system performance.
2Device complexity
If traditional allocation methods are used, then system simplicity is maintained, but task completion time increases
Solution Approach 1:
The router performs preliminary calculations of penalty scores for multiple possible robot assignments and route options before making the final allocation decision. By pre-evaluating different scenarios based on distance, traffic conditions, and robot capabilities, the system identifies the optimal assignment in advance, reducing overall task completion time without significantly increasing system complexity.
Solution Approach 2:
The allocation system dynamically adjusts robot assignments and route planning based on real-time system state information. The router continuously monitors robot positions, traffic conditions, and job requirements to make adaptive allocation decisions, optimizing task completion time while maintaining manageable system complexity through iterative improvements.
3Productivity
If multiple robots are allocated to jobs, then system productivity is improved, but allocation complexity increases
Solution Approach 1:
The patent transforms the complex multi-robot allocation problem into a series of simplified decisions by introducing penalty scores as a key parameter. The router calculates penalty scores based on distance, traffic wait times, and route complexity for each robot-job pairing, converting a complex optimization problem into a more manageable scoring and selection process that scales better with the number of robots.
Data Source
AI summary
A system for allocating jobs and/or targets to robots in an automated storage and retrieval system includes a plurality of robots and a framework structure forming a three-dimensional storage grid structure for storing containers. Each robot has wheels configured to move along two perpendicular horizontal directions on the grid. A central computer system manages robot movement and task allocation via a warehouse management system comprising an assigner and a router. The assigner generates lists of job and target options for each robot, which are made accessible to the router. The router assigns jobs and targets using a multi-position search algorithm based on each robot's location and the route required to reach the assigned job and target. This coordinated approach enables efficient task and path assignment within the storage system.