Warehouse Picking Route Planning Using Matrix Landmarks
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Solution Overview
Problem
Current path planning methods for unmanned devices in warehouses are inefficient, as they do not effectively determine the optimal route for picking operations, leading to suboptimal production efficiency.
Innovation Solution
A path planning method that uses a two-dimensional matrix map to determine the location of landmarks and calculate route distances, selecting the closest landmarks to the initial and target locations, and iteratively updating the current node to form a travel path, allowing for efficient route planning within the warehouse.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional path planning methods are used for unmanned devices in warehouses, then the routing can be determined, but the production efficiency is suboptimal due to inefficient route planning
Solution Approach 1:
The warehouse environment is segmented into a two-dimensional matrix map with discrete landmarks representing products and locations. This segmentation allows the path planning system to break down the complex routing problem into manageable segments (matrix cells, landmarks, and routes between them), enabling efficient computation of optimal paths while improving production efficiency
Solution Approach 2:
The system performs preliminary actions by pre-establishing the two-dimensional matrix map structure and pre-calculating possible routes between landmarks. When path planning is needed, the system can quickly query and select from pre-computed route options rather than calculating everything from scratch, thereby reducing route planning time while maintaining optimal paths
2Productivity
If the unmanned device visits all landmarks to pick products, then all products can be collected, but the travel path becomes excessively long and inefficient
Solution Approach 1:
The system changes the parameter representation from continuous coordinates to discrete matrix indices, and from absolute positions to relative landmark relationships. By representing the warehouse as a matrix with landmarks having specific indices, the system can efficiently calculate and compare path lengths using matrix distance metrics, enabling optimal route selection that minimizes travel path length while ensuring all necessary products are picked
3Productivity
If a complex routing algorithm is used to determine the optimal path, then the route efficiency can be improved, but the computational complexity and processing time increase
Solution Approach 1:
The system creates a simplified copy of the warehouse environment as a two-dimensional matrix map, where physical landmarks are represented as matrix elements with coordinates. This abstract copy allows the use of simpler matrix-based distance calculations and pathfinding algorithms instead of complex geometric computations, reducing algorithmic complexity while maintaining route optimization capability
Solution Approach 2:
The system transforms the three-dimensional physical warehouse space into a two-dimensional matrix representation. This dimensionality reduction simplifies the path planning problem by eliminating the need for complex 3D spatial calculations, allowing the use of efficient 2D matrix operations and algorithms to determine optimal routes while reducing computational complexity
Data Source
AI summary
A path planning method for an unmanned device includes taking a current landmark as a current node, obtaining a landmark corresponding to a product to be picked with a route closest to the current node, and taking the obtained landmark as the current node, wherein an initial value of the current node is an initial landmark of the unmanned device; determining whether the current node is a landmark corresponding to the last product to be picked; if no, performing the step of obtaining a landmark corresponding to a product to be picked with a route closest to the current node; and if yes, taking a route composed of the initial landmark of the unmanned device and landmarks corresponding to products to be picked that are selected sequentially as a travel route of the unmanned device.