- The development of software on embedded platforms poses challenges due to limited processing capabilities and high latency. This makes development time-consuming, especially in edge computing scenarios where real-time responsiveness is crucial. A streamlined installation process combined with a straightforward communication protocol minimizes setup time and accelerates development. The proposed solution leverages Docker containers to encapsulate essential software components on the edge device, offering a modular architecture that isolates functionalities and enables efficient configuration across heterogeneous environments. Integrating a communication protocol via MATLAB facilitates the development of complex algorithms on a high-performance platform—an approach widely used in mechatronic systems across mobility, manufacturing, and energy domains. To demonstrate this, a case study from research and teaching at TH Nürnberg is presented: sensors and a Raspberry Pi are integrated into a 1:10 scale RC vehicle. Communication with sensorsThe development of software on embedded platforms poses challenges due to limited processing capabilities and high latency. This makes development time-consuming, especially in edge computing scenarios where real-time responsiveness is crucial. A streamlined installation process combined with a straightforward communication protocol minimizes setup time and accelerates development. The proposed solution leverages Docker containers to encapsulate essential software components on the edge device, offering a modular architecture that isolates functionalities and enables efficient configuration across heterogeneous environments. Integrating a communication protocol via MATLAB facilitates the development of complex algorithms on a high-performance platform—an approach widely used in mechatronic systems across mobility, manufacturing, and energy domains. To demonstrate this, a case study from research and teaching at TH Nürnberg is presented: sensors and a Raspberry Pi are integrated into a 1:10 scale RC vehicle. Communication with sensors and actuators runs via Docker containers, enabling modular and reproducible deployment. Algorithms for autonomous driving—such as perception, planning, and motor control—are developed in MATLAB and transferred to the vehicle. This illustrates the flexibility of the approach for academic applications. It combines a fast, uniform hardware setup with a realistic scaled vehicle, well-suited for prototyping and experimentation in embedded systems.…
