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.