Centralized Sensor Data Generation for Multi-AGV Virtual Control
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Solution Overview
Problem
Existing technologies face challenges in simulating and controlling autonomous vehicles in dynamic environments, particularly in individualized production scenarios where autonomous vehicles like AGVs interact with dynamic components and cannot be predetermined.
Innovation Solution
A computer-implemented method and apparatus for generating sensor data using an environment model with a global coordinate system, which includes static and dynamic sensor positions, to create sensor data for autonomous vehicles. This sensor data is transformed into a local coordinate system for each vehicle and transmitted for control purposes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If sensor data is generated individually for each autonomous vehicle, then each vehicle can be controlled independently, but the system complexity and data synchronization between multiple vehicles deteriorates
Solution Approach 1:
The patent merges the sensor data generation process into a centralized simulation environment where all autonomous vehicles share a common virtual model. This allows individual vehicle control while maintaining system-wide coordination through the unified simulation framework, resolving the contradiction between independent control and system complexity.
Solution Approach 2:
The simulation environment serves multiple functions simultaneously: it generates sensor data for multiple vehicles, coordinates their interactions, and provides a unified control framework. This multi-functionality reduces overall system complexity while maintaining independent vehicle controllability.
2Device complexity
If deterministic production sequences are used, then simulation and control are simplified, but adaptability to dynamic components and individualized production deteriorates
Solution Approach 1:
The patent implements dynamic production sequences within the simulation environment where autonomous vehicles can adapt their paths and behaviors based on real-time conditions. The simulation model dynamically updates vehicle positions, sensor data, and environmental interactions, enabling adaptability to individualized production while maintaining manageable complexity through the virtual framework.
3Measurement precision
If optical sensors are used for environment recognition, then autonomous vehicles can define their state and position, but realistic sensor data for virtual commissioning and control is difficult to obtain
Solution Approach 1:
The patent creates a virtual copy of the real production environment including realistic sensor models that replicate the behavior of actual optical sensors. This virtual sensor data copying approach provides measurement precision for position and state determination while ensuring data realism for virtual commissioning, as the simulation accurately mimics real sensor characteristics and environmental interactions.
Data Source
AI summary
A method and an apparatus for generating sensor data for controlling an autonomous vehicle in an environment is provided, such as driverless transport vehicles in a factory for example. Sensor positions of static sensors and the sensors of autonomous vehicles are defined in a global coordinate system on the basis of an environment model, such as a BIM model for example. Sensor data is centrally generated in this global coordinate system for all sensors as a function of these sensor positions. The sensor data is then transformed into a local coordinate system of an autonomous vehicle and transferred for controlling the autonomous vehicle.