Virtual AGV Emulation for Routing and Device Interaction Testing
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Solution Overview
Problem
Existing AGV deployment and debugging processes are time-consuming, require factory shutdowns, and are highly dependent on personal experience, lacking comprehensive validation of interactions between AGVs and automated devices, leading to uncertainty and increased downtime.
Innovation Solution
A method and apparatus for emulating an AGV system that includes obtaining sensor data and device states in a virtual environment, controlling virtual AGV and device motion based on generated control information, and validating interactions, allowing for optimization of routing and scheduling algorithms.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If on-site validation and debugging is performed by an AGV deployment engineer, then the interaction between AGV and automated devices can be validated, but it takes a lot of time and efforts, and factory shutdown is required
Solution Approach 1:
The patent creates a virtual copy of the AGV system including virtual AGV, virtual automated devices, and virtual environment. This virtual model replicates the physical system's behavior and interactions, allowing comprehensive validation without affecting actual production. The virtual AGV system includes sensors, controllers, and routing algorithms that mirror the physical counterparts, enabling realistic scenario testing.
Solution Approach 2:
The patent performs validation and debugging activities in advance within the virtual environment before actual AGV deployment. By pre-validating interactions, optimizing routing algorithms, and testing edge cases in the virtual model, potential issues are resolved beforehand, eliminating the need for time-consuming on-site debugging and factory shutdowns.
2Reliability
If on-site validation and debugging is performed by an AGV deployment engineer, then the interaction between AGV and automated devices can be validated, but factory shutdown is required which affects normal production
Solution Approach 1:
The patent creates a virtual copy of the AGV system including virtual AGV, virtual automated devices, and virtual environment. This virtual model replicates the physical system's behavior and interactions, allowing comprehensive validation without affecting actual production. The virtual AGV system includes sensors, controllers, and routing algorithms that mirror the physical counterparts, enabling realistic scenario testing.
Solution Approach 2:
The virtual environment acts as an intermediary between the AGV deployment process and the actual factory operations. It provides a sandbox for testing and validation that is isolated from production systems, allowing engineers to validate interactions and optimize parameters without interrupting normal factory workflows.
3Ease of manufacture
If existing emulator is used to validate AGV controller or routing algorithm separately, then partial validation can be performed, but comprehensive validation of entire AGV system and interaction with automated devices cannot be achieved
Solution Approach 1:
The patent merges multiple validation capabilities into a single integrated virtual environment. It combines AGV controller validation, routing algorithm validation, sensor validation, and interaction validation with automated devices into one unified virtual AGV system. This integration allows comprehensive validation of the entire system simultaneously, rather than requiring separate validation processes for each component.
Solution Approach 2:
The virtual AGV system is designed to perform multiple validation functions simultaneously. It can validate the AGV controller, routing algorithms, sensor data processing, and interactions with various automated devices all within the same environment. The virtual environment supports diverse validation scenarios including normal operations, edge cases, and failure conditions.
4Productivity
If AGV deployment is performed without comprehensive validation, then deployment speed can be maintained, but uncertainty in downtime estimation increases and personal experience dependency increases
Solution Approach 1:
The patent performs validation and debugging activities in advance within the virtual environment before actual AGV deployment. By pre-validating interactions, optimizing routing algorithms, and testing edge cases in the virtual model, potential issues are resolved beforehand, eliminating the need for time-consuming on-site debugging and factory shutdowns.
Solution Approach 2:
The virtual environment provides comprehensive feedback on AGV system performance, interaction validity, and routing efficiency before actual deployment. This feedback mechanism allows engineers to identify and correct issues, optimize parameters, and predict deployment outcomes with high accuracy, reducing uncertainty and dependency on personal experience.
Data Source
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AI summary
A method for emulating an automated guided vehicle (AGV) system including: 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; and controlling motion of the virtual AGV and the virtual device. With the method, time and efforts 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.