Virtual Facility Simulation for Robot Fleet and Inventory Control
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Solution Overview
Problem
Existing robotics systems face challenges in integrating, controlling, and simulating operations efficiently, particularly in large facilities like warehouses, leading to tedious and non-scalable robot navigation map creation and high inventory shrinkage due to reliance on barcode scanners prone to human error.
Innovation Solution
A virtual facility system is developed, comprising a storage system, data engine, integration system, and simulator engine, which creates a photorealistic 3D representation of the real facility, integrates with control systems, and simulates future states, allowing for efficient robot fleet management and inventory tracking using visual and spatial data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional barcode scanners and manual methods are used for inventory tracking and robot navigation, then implementation is simple and familiar, but human error increases and scalability is limited
Solution Approach 1:
The patent replaces traditional barcode scanning mechanisms with vision-based systems using cameras and neural rendering models. The system captures images of inventory items and uses AI-powered image processing to identify, locate, and track items without physical contact or line-of-sight requirements, thereby eliminating scanner complexity while improving accuracy.
Solution Approach 2:
The system creates virtual copies of the physical facility through photorealistic 3D representations and digital twins. These virtual models replicate the facility layout, inventory positions, and robot locations, allowing for simulation and analysis without physically implementing complex tracking infrastructure in the real world.
2Loss of information
If photorealistic 3D representations and neural rendering models are implemented, then observability and simulation capability improve, but computational resources and processing time increase
Solution Approach 1:
The system implements multi-fidelity rendering where photorealistic neural rendering is applied selectively to specific regions or items of interest rather than the entire facility. For areas requiring detailed observation, high-fidelity rendering is used, while other areas use lower-fidelity representations, balancing observability with computational efficiency.
Solution Approach 2:
The facility is divided into multiple zones or regions, each with its own level of rendering detail. The system processes and renders only the necessary portions of the facility at high fidelity at any given time, reducing overall computational load while maintaining observability where needed.
3Reliability
If simulation of future states is implemented for robot fleet management, then operational planning and safety improve, but simulation time and computational overhead increase
Solution Approach 1:
The system performs simulation and analysis of future states before actual robot operations begin. By pre-simulating robot paths, potential conflicts, and operational scenarios in the virtual facility model, the system identifies and resolves safety issues beforehand, reducing the need for time-consuming real-time adjustments and re-simulations.
Solution Approach 2:
The system uses accelerated simulation techniques that skip through time in the virtual environment, allowing rapid evaluation of multiple future states and scenarios. This enables comprehensive safety analysis without proportionally increasing real-time computational burden.
Data Source
AI summary
A virtual facility system may include a storage system, a data engine, an integration system, a virtual facility interface system, and a simulator engine. The storage system may store data including video of the real facility. The data engine may train a neural rendering model of the real facility based on the data providing a photorealistic three-dimensional representation of the real facility. The integration system may provide one or more interfaces facilitating communication with one or more control systems associated with the real facility including a management system providing historical or live inventory tracking data and facility operations process data characterizing of locations and tasks corresponding with inventory items or materials stored or handled in the real facility. The virtual facility interface system may provide access to information stored in a virtual facility. The simulator engine may simulate novel views generated based on the neural rendering model.