AGV Parking Point Scheduling for Balanced Warehouse Dispatch
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Solution Overview
Problem
Current methods lack an effective way to schedule automated guided vehicles (AGVs) in human-machine collaborative order picking modes, leading to inefficiencies in warehousing operations due to the lack of a systematic approach for allocating AGVs to temporary parking points.
Innovation Solution
A method and device for scheduling AGVs that involve acquiring information about temporary parking points and AGVs, calculating the number of missing vehicles at each point, filtering out idle or unavailable points, and scheduling AGVs to a target point based on the number of missing vehicles, considering factors like time consumption and task boxes to be conveyed.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual order picking and cart pushing is used, then flexibility in handling task boxes is maintained, but time consumption and physical strength requirements increase significantly
Solution Approach 1:
The system enables automated guided vehicles to autonomously navigate, transport task boxes, and return to parking points without human intervention. The AGVs self-manage their routes, task box handling, and positioning, eliminating the need for manual cart pushing while maintaining operational flexibility through programmable navigation and adaptive route planning.
Solution Approach 2:
The patent replaces the manual mechanical system of cart pushing with an automated guided vehicle system that uses sensors, controllers, and automated navigation. The mechanical action of human-powered cart transport is substituted with automated vehicles equipped with guidance systems, task box grippers, and autonomous navigation capabilities, significantly reducing physical strength requirements.
2Productivity
If AGV vehicles are deployed for conveying task boxes, then operating efficiency improves, but the lack of effective scheduling methods leads to suboptimal resource allocation
Solution Approach 1:
The scheduling system pre-calculates optimal parking points for AGV vehicles based on current task box locations, delivery line port status, and vehicle availability. By performing scheduling computations in advance rather than reactively, the system optimizes resource allocation before AGVs need to be dispatched, improving operating efficiency while managing complexity through proactive planning.
Solution Approach 2:
The system continuously monitors the status of AGV vehicles, task box locations, and delivery line port conditions, using this feedback to dynamically adjust scheduling decisions. The scheduling method incorporates real-time status information to optimize vehicle allocation to parking points, ensuring that the system adapts to changing conditions while maintaining efficient resource utilization.
3Ease of operation
If AGV vehicles are scheduled to temporary parking points without systematic methods, then vehicle deployment is simplified, but imbalances between idle and busy points increase
Solution Approach 1:
The scheduling system dynamically adjusts parameters such as parking point selection, vehicle assignment, and task box allocation based on real-time system conditions. By changing these parameters systematically according to measured imbalances between idle and busy points, the method maintains simplicity in vehicle deployment while stabilizing the overall system composition and preventing extreme imbalances.
Solution Approach 2:
The scheduling method transitions from static vehicle deployment to dynamic allocation, where parking point assignments and vehicle routes are continuously adjusted based on current system state. This dynamic approach allows the system to respond to changing conditions while maintaining operational simplicity through automated decision-making, balancing the distribution of AGVs across different parking points.
Data Source
AI summary
A method and device for scheduling automated guided vehicles. One method includes acquiring, based on a task for scheduling automated guided vehicles, information of a set of temporary parking points and information of automated guided vehicles; calculating, based on the information of the set of temporary parking points and the information of automated guided vehicles, the number of missing vehicles at each temporary parking point in the set of temporary parking point; selecting, based on the number of missing vehicles, a target temporary parking point from the set of temporary parking points, and scheduling the automated guided vehicles to be scheduled to the target temporary parking point.