Directed Graph Pathway Model for Physical System Navigation
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Solution Overview
Problem
Determining the shortest path between locations in complex physical systems is challenging due to the complexity of interactions and frequent changes in the physical environment, making existing methods time-consuming and requiring skilled computational scientists.
Innovation Solution
A method involving the generation of a pathway model using a directed graph based on cell-based layout tables, where components of the graph are defined by associating them with cell locations and configuring them based on attribute descriptors, allowing for the generation of pathways between reference locations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional optimization methods are used to determine shortest paths in complex physical systems, then path determination accuracy is improved, but time consumption increases and requires highly skilled computational scientists
Solution Approach 1:
The patent creates a virtual digital twin model that copies the physical system's structure, constraints, and dynamics. This virtual model can be simulated repeatedly to determine optimal paths without physically traversing the complex environment, thereby achieving accurate path determination while reducing time consumption.
Solution Approach 2:
The patent replaces physical trial-and-error navigation with computational simulation. Instead of using skilled computational scientists to manually optimize paths through complex systems, the system uses automated virtual modeling and simulation to determine optimal pathways, substituting mechanical problem-solving with digital computation.
2Device complexity
If static cell-based representations are used to model physical systems, then system representation simplicity is improved, but the ability to reveal complex interactions and traffic patterns deteriorates
Solution Approach 1:
The patent transforms static cell-based representations into dynamic virtual twin models that can simulate system behavior over time. This allows the model to capture traffic patterns, congestion, and complex interactions that arise from temporal variations in system state, while maintaining the structured approach of cell-based organization.
Solution Approach 2:
The patent adds temporal and behavioral dimensions to the traditional spatial cell-based representation. By simulating system dynamics across multiple time steps and scenarios, the model reveals complex interactions and traffic patterns that are not visible in static representations, effectively adding new dimensions of analysis.
3Stability of the object's composition
If previously determined routes are used in physically changing environments, then route stability is improved, but route validity deteriorates due to obsolescence from physical changes
Solution Approach 1:
The patent implements dynamic route planning where paths are continuously updated based on current system state captured in the virtual twin model. This allows the system to adapt routes to physical changes such as moved shelving, added conveyor belts, or altered intersections, maintaining route validity while providing stability through automated updates.
Solution Approach 2:
The patent uses feedback from continuous monitoring of the physical system to update the virtual twin model and recalibrate optimal paths. This feedback loop ensures that routes remain valid by incorporating real-time information about physical changes, while maintaining stability through systematic, automated updates rather than ad-hoc modifications.
Data Source
AI summary
Pathways between reference locations in a physical system are generated based on a layout table. Nodes and edges of the directed graph are associated with cell locations of the layout table. The cell locations define features of the reference locations. Parameters of the nodes and edges are defined based on descriptors recalled from the cells associated with the nodes and edges. The nodes and edges are configured based on the descriptors. Path data regarding potential pathways is generated based on the defined nodes and edges.