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This paper reports on the use of co-simulation techniques to build prototypes of co-operative autonomous robotic cyber-physical systems. Designing such systems involves a mission-specific planner algorithm, a control algorithm to drive an agent performing its task; and the plant model to simulate the agent dynamics. An application aimed at positioning a swarm of unmanned aerial vehicles (drones) in a bounded area, exploiting a Voronoi tessellation algorithm developed in this work, is taken as a case study. The paper shows how co-simulation allows testing the complex system at the design phase using models created with different languages and tools. The paper then reports on how the adopted co-simulation platform enables control parameters calibration, by exploiting design space exploration technology. The INTO-CPS co-simulation platform, compliant with the Functional Mock-up Interface standard to exchange dynamic simulation models using various languages, was used in this work. The different software modules were written in Modelica, C, and Python. In particular, the latter was used to implement an original variant of the Voronoi algorithm to tesselate a convex polygonal region, by means of dummy points added at appropriate positions outside the bounding polygon. A key contribution of this case study is that it demonstrates how an accurate simulation of a cooperative drone swarm requires modeling the physical plant together with the high-level coordination algorithm. The coupling of co-simulation and design space exploration has been demonstrated to support control parameter calibration to optimize energy consumption and convergence time to the target positions of the drone swarm. From a practical point of view, this makes it possible to test the ability of the swarm to self-deploy in space in order to achieve optimal detection coverage and allow unmanned aerial vehicles in a swarm to coordinate with each other.

Recent advancements in the automotive field have significantly increased the level of complexity and connectivity of modern vehicles. In this context, the topic of cybersecurity becomes extremely relevant, as a successful attack can have an impact in terms of safety on the car navigation, potentially leading to harmful behavior. Risk assessment is typically performed using discrete input and output scales, which can often lead to an identical output in terms of risk evaluation despite the inputs presenting non-negligible differences. This work presents a novel fuzzy-logic-based methodology to assess cybersecurity risks which takes attack feasibility and safety impact as input factors. This technique allows us explicitly model the uncertainty and ambiguousness of input data, which is typical of the risk assessment process, providing an output on a more detailed scale. The fuzzy inference engine is based on a set of control rules expressed in natural language, which is crucial to maintaining the interpretability and traceability of the risk calculation. The proposed framework was applied to a case study extracted from ISO/SAE 21434. The obtained results are in line with the traditional methodology, with the added benefit of also providing the scatter around the calculated value, indicating the risk trend. The proposed method is general and can be applied in the industry independently from the specific case study.

We are concerned with systems, particularly safety-critical systems, that involve interaction between users and devices, such as the user interface of medical devices. We therefore developed a MISRA C code generator for formal models expressed in the PVSio-web prototyping toolkit. PVSio-web allows developers to rapidly generate realistic interactive prototypes for verifying usability and safety requirements in human-machine interfaces. The visual appearance of the prototypes is based on a picture of a physical device, and the behaviour of the prototype is defined by an executable formal model. Our approach transforms the PVSio-web prototyping tool into a model-based engineering toolkit that, starting from a formally verified user interface design model, will produce MISRA C code that can be compiled and linked into a final product. An initial validation of our tool is presented for the data entry system of an actual medical device.

Mechatronic systems are a class of cyber-physical systems, whose increasing complexity makes their validation and verification more and more difficult, while their requirements become more challenging. This paper introduces a development method based on model-based design, co-simulation and formal verification. The objective of this paper is to show the applicability of the method in an industrial setting. An application case study comes from the field of precision servo-motors, where formal verification has been used to find acceptable intervals of values for design parameters of the motor controller, which have been further explored using co-simulation to find optimal values. The reported results show that the method has been applied successfully to the case study, augmenting the current model-driven development processes by formal verification of stability, formal identification of acceptable parameter ranges, and automatic design-space exploration.