Uwe Pohlmann

The MechatronicUML method: model-driven software engineering of self-adaptive mechatronic systems

The software of mechatronic systems interacts with the systems physical environment. In such systems, an incorrect software may cause harm to human life. As a consequence, software engineering methods for developing such software need to enable developers to effectively and efficiently proof their correctness. This is further complicated by additional characteristics of mechatronic systems as self-adaptation and coordination with other systems. In this poster, we present MechatronicUML which is a model-driven software engineering method that especially considers these characteristics of self-adaptive mechatronic systems.

A tool suite for the model-driven software engineering of cyber-physical systems

Cyber-physical systems, e.g., autonomous cars or trains, interact with their physical environment. As a consequence, they commonly have to coordinate with other systems via complex message communication while realizing safety-critical and real-time tasks. As a result, those systems should be correct by construction. Software architects can achieve this by using the MechatronicUML process and language. This paper presents the MechatronicUML Tool Suite that offers unique features to support the MechatronicUML modeling and analyses tasks.

Viewpoints and Views in Hardware Platform Modeling for Safe Deployment

Future cyber-physical systems will behave smart, i.e., they will provide self-* properties and collaborate with each other. Software realizes this smart behavior. In modern cars, a hardware platform consists of up to 100 networked electronic control units (ECUs) that execute the software. As the amount of safety-critical software increases, the task of describing a suitable hardware platform for deploying safety-critical software components to ECUs becomes more complicated. Existing approaches for the definition of a hardware platform do not address the different stakeholders concerns and do not provide a systematic method. This leads to an error-prone development. In this paper, we identify viewpoints for the stakeholders concerns and provide a method for the multi-view modeling of hardware platforms. In addition, we support hierarchical and variable horizontal composition of hardware platforms by transferring concepts from component-based software engineering. To test our method, we use an Arduino-based cooperative adaptive cruise control system.

Application of an intelligent network architecture on a cooperative cyber-physical system: An experience report

Cooperative cyber-physical systems (CCPS) are driven by the tight coordination between computational components, physical sensors and actuators, and the interaction with each other over system bounds. The software development of CCPS is getting more complex because of the tight integration, heterogeneous technologies, as well as safety and timing requirements. Therefore, new engineering approaches, such as model-driven development methods, are required, along with communication architectures with self-* capabilities. Both will support the developer in specifying such a system effectively and efficiently. However, the application of such techniques for the development of CCPS has not been addressed sufficiently so far. This paper presents an experience report of developing a cooperative delta-robot system that juggles a ball without a central control or camera system. For the development, an intelligent network architecture and model-driven development method for CCPS are applied.