Autonomous Storage Unit Boarding Order for Low-Latency Inventory Transport
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Solution Overview
Problem
Current autonomous inventory management systems face challenges in scalability, latency, and limited intelligence, particularly in adapting to inventory demands and environmental conditions, leading to inefficiencies in transportation and storage operations.
Innovation Solution
A system and method for controlling autonomous inventory management, utilizing hardware processors configured by machine-readable instructions to direct transport systems to transport autonomous storage units between locations, determining drop-off locations, and optimizing boarding orders, incorporating navigation, sensing, and control devices to enhance operational efficiency and adaptability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If centralized processing systems are used to control robot fleets and transportation systems, then coordination and control are simplified, but scalability is limited and latency increases
Solution Approach 1:
The system divides the centralized processing architecture into distributed edge computing nodes deployed across multiple geographic sites. Each edge node processes local inventory management tasks autonomously, while still coordinating with other nodes through standardized communication protocols. This segmentation enables the system to scale across multiple locations without overloading a single central processor, reducing latency while maintaining coordination capabilities.
2Ease of manufacture
If current robots and transportation systems are used, then existing infrastructure is maintained, but adaptability to inventory demands and environmental conditions is limited
Solution Approach 1:
The patent implements dynamic task allocation and routing systems that allow robots and transportation units to adapt their behavior in real-time based on changing inventory demands, environmental conditions, and system state. The edge computing nodes continuously analyze local conditions and dynamically adjust task assignments, route planning, and resource allocation, enabling the system to respond flexibly to varying requirements while operating within existing infrastructure constraints.
3Area of stationary object
If autonomous storage units are deployed across multiple geographic sites, then inventory management coverage is expanded, but system complexity and communication requirements increase
Solution Approach 1:
The system employs universal standardized communication protocols and interfaces that enable autonomous storage units and edge computing nodes to operate consistently across multiple geographic sites. The modular edge node architecture provides multi-functional capabilities including local task management, data processing, and inter-site coordination through standardized protocols, reducing system complexity despite expanded geographic coverage.
4Loss of time
If real-time autonomous decision-making is implemented, then response time to inventory demands is reduced, but processing requirements and computational load increase
Solution Approach 1:
The patent introduces edge computing nodes as intermediary processing layers between the autonomous storage units and central cloud systems. These edge nodes perform real-time data processing and autonomous decision-making locally at each geographic site, reducing the computational load on individual storage units and eliminating the need for constant cloud communication. This intermediary architecture enables fast local responses while distributing the overall computational burden across multiple edge nodes.
Data Source
AI summary
Systems, methods, computing platforms, and storage media for controlling an autonomous inventory management system are disclosed. Exemplary implementations may: direct a first transport system to a first location; determine a respective drop off location for each of the one or more autonomous storage units; determine a boarding order for the one or more autonomous storage units based at least in part on the respective drop off location for each of the one or more autonomous storage units; direct the one or more autonomous storage units to board the first transport system at the first location; and transport the one or more autonomous storage units from the first location to the one or more respective drop off locations.