Virtual AGV Emulation for Full-System Interaction Validation
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Solution Overview
Problem
Current methods for validating and debugging automated guided vehicles (AGVs) in industrial environments are time-consuming, require factory shutdowns, and are heavily dependent on personal experience, failing to simultaneously validate the interaction between AGVs and other automated devices, and are inconsistent with actual conditions.
Innovation Solution
A method and apparatus for emulating an AGV system that includes obtaining sensor data and determining device states in a virtual environment, sending this data to the AGV system to receive motion control information, and controlling virtual AGV and device motion, allowing for the validation and debugging of the entire AGV system, including interactions with other automated devices.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If on-site validation and debugging is performed by deployment engineers, then interaction between AGV and automated devices can be validated, but it takes a lot of time and efforts and requires factory shutdown
Solution Approach 1:
The patent creates a virtual copy of the AGV system including virtual AGV, virtual automated devices, and virtual environment that replicates the physical factory layout. This virtual model allows complete validation and debugging of AGV interactions without affecting the actual factory operations, thus eliminating the need for factory shutdown while maintaining validation reliability
Solution Approach 2:
The system performs validation and debugging in advance within the virtual environment before actual AGV deployment. All interaction scenarios, routing algorithms, and scheduling optimizations are tested beforehand, so that when the actual deployment occurs, no extensive on-site debugging is needed, significantly reducing deployment time and factory downtime
2Reliability
If on-site debugging is performed according to engineer experience, then AGV interaction can be validated, but it brings great uncertainty to estimation of factory downtime
Solution Approach 1:
By creating a faithful virtual replica of the AGV system and environment, the patent enables systematic and repeatable validation processes that are not dependent on individual engineer experience. The virtual model allows consistent testing under controlled conditions, making deployment time estimation predictable and certain
Solution Approach 2:
All validation and optimization work is completed in advance within the virtual environment using systematic algorithms rather than experience-based trial and error. This preliminary validation ensures that deployment time can be accurately estimated beforehand, eliminating the uncertainty associated with experience-dependent debugging
3Ease of manufacture
If existing emulator is used to validate AGV controller or routing algorithm separately, then partial validation can be performed, but the entire AGV system and interaction with automated devices cannot be validated simultaneously
Solution Approach 1:
The patent merges the validation of AGV controller, routing algorithm, scheduling manager, and interactions with automated devices into a single integrated virtual environment. All these components work together in the virtual model, allowing simultaneous and comprehensive validation of the entire AGV system rather than separate partial validations
Solution Approach 2:
The virtual environment serves multiple validation functions simultaneously: it validates AGV controller behavior, tests routing algorithms, optimizes scheduling, and simulates interactions with various automated devices. This multi-functional virtual platform provides complete system validation in one unified environment
4Ease of operation
If AGV controller is fully virtualized in emulator, then validation can be performed, but emulation result depends on manually set parameters and is generally inconsistent with actual situation
Solution Approach 1:
The patent creates a comprehensive virtual model that copies not only the AGV controller but also the automated devices, factory environment, sensor data generation, and interaction logic. This faithful replication ensures that emulation results accurately reflect actual system behavior, eliminating the inconsistency problem of partial virtualization with manually set parameters
Data Source
AI summary
A method for emulating an automated guided vehicle (AGV) system includes: obtaining sensor data of a virtual AGV in an emulation environment; determining a device state of a virtual device interacting with the virtual AGV in the emulation environment; sending the sensor data and the device state to the AGV system, and receiving AGV motion control information and device operation information from the AGV system. The AGV motion control information and the device operation information are generated by the AGV system based on the sensor data and the device state. The motion of the virtual AGV and the virtual device is controlled in the emulation environment based on the AGV motion control information and the device operation information, respectively. Time and effort spent by a deployment engineer on deployment and debugging are reduced, factory downtime is decreased, and an entire AGV system and an AGV sensor can be validated.