Container Vehicle Routing With Partial Route Locking
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Solution Overview
Problem
Existing automated storage and retrieval systems face challenges in efficiently routing and rerouting container handling vehicles on a grid-based rail system, particularly in dynamically changing environments where vehicles may change tasks or new vehicles are introduced, leading to inefficiencies and increased waiting times.
Innovation Solution
A method that calculates routes on the fly as vehicles move, allowing for frequent rerouting and the creation of new routes for active vehicles. This approach uses multi-agent pathfinding (MAPF) algorithms to find routes for all vehicles, but only locks the first part of each route for a set time interval, enabling more flexible and efficient route adjustments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Stability of the object's composition
If complete routes are locked for container handling vehicles, then route stability is improved, but route flexibility and adaptability deteriorate
Solution Approach 1:
The patent divides the route into segments: a locked first part that provides stability and a_unlocked second part that allows flexibility. This segmentation enables different portions of the route to have different levels of commitment, resolving the contradiction between stability and adaptability.
Solution Approach 2:
The patent implements dynamic route locking where the extent of the locked first part varies based on traffic conditions, vehicle priorities, and system state. This dynamic adjustment allows the system to adapt the degree of route stability needed at different times, balancing stability and flexibility.
2Loss of time
If routes are calculated and locked in advance, then computational time is reduced, but route alternatives and system responsiveness deteriorate
Solution Approach 1:
The patent performs preliminary route calculation for the first part of the route in advance, locking it to reduce future computational needs. This preliminary action balances upfront computation with later adaptability, as the second part remains unlocked for future optimization.
Solution Approach 2:
The patent calculates and locks only a portion (the first part) of the complete route rather than the entire route. This partial action reduces computational burden while preserving flexibility for the remaining portion, addressing the trade-off between computation time and route alternatives.
3Adaptability or versatility
If frequent rerouting is allowed, then system adaptability improves, but computational complexity and traffic coordination difficulty worsen
Solution Approach 1:
By segmenting the route into locked and unlocked parts, the patent limits the scope of rerouting calculations to only the second part. This segmentation reduces computational complexity compared to recalculating entire routes, while still allowing frequent rerouting where needed.
Solution Approach 2:
The patent applies different levels of routing flexibility to different parts of the system: the first part has fixed quality (locked) while the second part has variable quality (unlocked). This local differentiation reduces overall computational complexity by restricting complex calculations to only where necessary.
4Volume of moving object
If the rail system uses a grid-based structure, then space utilization improves, but routing complexity and vehicle coordination worsen
Solution Approach 1:
The patent segments the grid-based rail system into zones with different routing rules: areas with locked routes provide predictable paths while areas with unlocked routes allow flexible adaptation. This segmentation manages routing complexity in the grid structure.
Solution Approach 2:
The patent implements dynamic route locking on the grid system, allowing the degree of routing fixation to change based on local conditions. This dynamic approach simplifies coordination in high-traffic grid intersections while maintaining flexibility where needed.
Data Source
AI summary
A method, control system and computer program for routing and rerouting of container handling vehicles handling storage containers in an automated storage and retrieval system comprising a framework structure forming a three-dimensional storage grid structure for storing the storage containers in storage columns, the framework structure including a grid-based rail system arranged above the storage columns with the rail system providing available routes for the container handling vehicles handling and transferring the storage containers to and from the storage columns, and wherein each container handling vehicle comprises a first set of wheels configured to move the vehicle along a first lateral direction (X) of the grid-based rail system and a second set of wheels configured to move the vehicle along a second lateral direction (Y) of the grid-based rail system, the second direction (Y) being perpendicular to the first direction (X), the movements of the container handling vehicles being controlled by a control system, that determines which tasks are to be done by specified container handling vehicles, destination locations for performing the tasks and which routes the container handling vehicles are to travel on the rail system. The method comprises the following steps performed by the control system when executing the computer program: running a multi-agent pathfinding algorithm, MAPF, in the control system for establishing and assigning routes on the rail system for the container handling vehicles from their current locations to assigned tasks at destination locations; determining how far the container handling vehicles can travel on a first part of the assigned routes within a set time interval, the first part being shorter than the assigned routes to the destinations; locking the first parts of the assigned routes that the container handling vehicles can travel within the set time interval; instructing the container handling vehicles to move from their current locations to an end location on the assigned locked routes; repeating steps above.