Node Reduction for Optimal Pathfinding in Logistics Automation

Solution Overview

Problem

Conventional logistics automation systems face excessive computation time and load due to the exponential increase in execution time of algorithms like Dijkstra's and A* as the number of nodes increases, leading to increased server load and decreased operation efficiency.

Innovation Solution

A method and system for node reduction that converts a conventional graph into a representative node graph, using representative nodes connected to three or more edges, calculating representative node paths, and applying Dijkstra's or A* algorithm to reduce computation time and load.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If Dijkstra's algorithm or A* algorithm is used to calculate the shortest path in a graph with a large number of nodes, then the path calculation accuracy is improved, but the execution time increases exponentially and server load increases

Engineering Contradiction:

Improvepath calculation accuracyVSAvoidexecution time

Core Design Contradiction:

Measurement precisionVSLoss of time

Solution Approach 1:

The patent segments the graph into multiple subgraphs based on spatial proximity, where each subgraph contains a subset of nodes and their connecting edges. By dividing the large-scale graph into smaller manageable subgraphs, the algorithm only needs to perform path calculations within these smaller segments, dramatically reducing the computational complexity from O(V²) or O(E+VlogV) on the full graph to much smaller values on individual subgraphs, thus resolving the contradiction between path accuracy and execution time

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The patent introduces a spatial dimension by calculating Euclidean distances between nodes and using this geometric information to determine subgraph membership and boundary conditions. This dimensional approach allows the system to leverage spatial locality, where nodes that are physically close are more likely to be part of the same subgraph, enabling efficient path calculations while maintaining accuracy for paths that span multiple subgraphs by using boundary node transitions

Inventive Principle:

Principle #17Another dimension (Dimensionality change)

2Adaptability or versatility

If the number of nodes in the graph increases to cover a larger task space, then the system coverage is improved, but the computation load of the server increases

Engineering Contradiction:

Improvesystem coverageVSAvoidcomputation load

Core Design Contradiction:

Adaptability or versatilityVSDevice complexity

Solution Approach 1:

The patent segments the large-scale graph into multiple smaller subgraphs based on spatial proximity, where each subgraph contains a subset of nodes and their connecting edges. By dividing the large-scale graph into smaller manageable subgraphs, the algorithm only needs to perform path calculations within these smaller segments, dramatically reducing the computational complexity from O(V²) or O(E+VlogV) on the full graph to much smaller values on individual subgraphs, thus resolving the contradiction between path accuracy and execution time

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The patent introduces a spatial dimension by calculating Euclidean distances between nodes and using this geometric information to determine subgraph membership and boundary conditions. This dimensional approach allows the system to leverage spatial locality, where nodes that are physically close are more likely to be part of the same subgraph, enabling efficient path calculations while maintaining accuracy for paths that span multiple subgraphs by using boundary node transitions

Inventive Principle:

Principle #17Another dimension (Dimensionality change)

3Reliability

If the graph includes all nodes in the task space, then the path calculation completeness is improved, but the control request-response time between server and logistics robot increases

Engineering Contradiction:

Improvepath calculation completenessVSAvoidcontrol request-response time

Core Design Contradiction:

ReliabilityVSSpeed

Solution Approach 1:

The patent segments the graph into multiple subgraphs based on spatial proximity, where each subgraph contains a subset of nodes and their connecting edges. By dividing the large-scale graph into smaller manageable subgraphs, the algorithm only needs to perform path calculations within these smaller segments, dramatically reducing the computational complexity from O(V²) or O(E+VlogV) on the full graph to much smaller values on individual subgraphs, thus resolving the contradiction between path accuracy and execution time

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The patent performs preliminary actions by pre-calculating and storing subgraph structures, boundary nodes, and transition information before actual path queries are made. This preprocessing allows the system to quickly respond to path calculation requests by utilizing the pre-organized subgraph data, reducing the real-time computational burden and improving control request-response times while maintaining complete path calculation capability across the entire task space

Inventive Principle:

Principle #10Preliminary action

Data Source

PatentUS20250335835A1Method, apparatus, and system for calculating optimal path on basis of node reduction

Publication Date: 2025.10.30 DAIM RES CO LTD

AI summary

The present invention relates to a method, an apparatus, and a system for calculating an optimal path on the basis of node reduction and, more specifically, to a method, an apparatus, and a system for calculating an optimal path on the basis of node reduction, in which an optimal path from a departure node to a destination node can be effectively calculated on the basis of a graph including multiple nodes corresponding to a task space in a logistics automation system.