Automated Movement Orchestration Using Physical Graphs
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Solution Overview
Problem
Current technologies lack the ability to automatically and efficiently orchestrate the concurrent movement of physical entities within a physical space, considering the semantic understanding of the space and entities, while honoring physical constraints and adapting to changes in movement compliance.
Innovation Solution
A physical graph is used to formulate a plan for concurrent movement of physical entities, which is orchestrated by communicating instructions and continuously monitored for compliance, with alternative plans constructed as needed to ensure adherence to physical constraints and optimize movement.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If automated movement orchestration is implemented for multiple physical entities, then productivity and efficiency of space utilization is improved, but device complexity and computational requirements increase
Solution Approach 1:
The system segments the physical space into discrete zones and represents each physical entity as an individual node in a graph structure. This segmentation allows the complex problem of multi-entity movement orchestration to be broken down into manageable components, where each entity can be tracked and controlled independently while still contributing to the overall system optimization.
Solution Approach 2:
A computational intermediary system acts as a mediator between physical entities and the orchestration logic. This intermediary maintains the physical graph representation, evaluates movement plans, and communicates instructions to entities. It handles the computational complexity centrally, allowing individual entities to remain relatively simple while the system as a whole achieves high productivity.
2Adaptability or versatility
If semantic understanding of physical space is incorporated into movement planning, then adaptability and decision-making capability are improved, but measurement precision and detection requirements increase
Solution Approach 1:
The system performs preliminary action by pre-establishing the physical graph representation of the space and entities before movement orchestration begins. This pre-computed semantic understanding includes spatial relationships, entity characteristics, and constraints, which are prepared in advance to enable rapid adaptive decision-making during actual movement operations without requiring real-time re-detection of all parameters.
Data Source
AI summary
The automatic formulation of a plan for concurrent movement of physical entities within a physical space. A physical graph is used to formulate such a plan. The physical graph represents multiple physical entities that have been sensed in a physical space over time. A plan is then formulated based on an evaluation of that physical graph. Such plans are enabled by the semantic understanding of the physical space and its contents that the physical graph provides. The plan honors physical constraints of the physical space, and physical constraints of the physical entities that are moving within that physical space. The plan may be further orchestrated by communicating with the physical entities to provide instructions for movement. Then, movement is monitored to determine if the plan is being complied with. If the plan is not being complied with, further communications are made and/or an alternative plan is automatically constructed.