用于多模态传感器网络高效物理仿真的高可扩展和广义传感器结构

Jörn Thieling, J. Roßmann
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引用次数: 8

摘要

多模态传感器网络用于各种应用领域,以实现高度自动化和自主系统。由于传感器数量的增加和整个系统的复杂性,我们建议使用虚拟试验台(vtb),它允许在整个开发过程中进行全面的虚拟系统测试。在这里,vtb被用作一个软件环境,在其中,真实技术系统的“数字孪生”在其操作环境中进行建模和模拟。在这篇文章中,我们描述了一个高度可扩展的传感器框架,这些vtb使用它来实现各种传感器类型(例如摄像头、激光雷达、雷达和超声波传感器)的高效物理模拟。在这种情况下,我们提出了基于相同数据库的通用传感器结构,以减少冗余并确保不同传感器类型和制造商之间的一致性。此外,这些高度可扩展的传感器结构与现代gpu相结合,以实现来自各个领域的传感器应用程序的高效和交互式模拟。
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Highly-Scalable and Generalized Sensor Structures for Efficient Physically-Based Simulation of Multi-Modal Sensor Networks
Multi-modal sensor networks are used in various fields of application to allow for highly-automated and autonomous systems. Due to the increasing number of sensors and overall system complexity, we propose the use of Virtual Testbeds (VTBs) which allow for comprehensive virtual system tests throughout the development process. Here, VTBs are used as a software environment in which “Digital Twins” of real technical systems are modeled and simulated within their operational environment. In this contribution, we describe a highly-scalable sensor framework used by those VTBs to enable efficient physically-based simulations of various sensor types (e.g. camera, LiDAR, RADAR and ultrasonic sensors). In this context, we present generalized sensor structures that are acting on the same data base to reduce redundancy and ensure consistency across different sensor types and manufacturers. Furthermore, those highly-scalable sensor structures are combined with modern GPUs to achieve efficient and interactive simulations of sensor-enabled applications from various domains.
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