Biblio

Recent years have witnessed several educational innovations to provide effective and engaging classroom instruction with the integration of immersive interactions based on augmented reality and virtual reality (AR/VR). This paper outlines the development of an ARCore-based application (app) that can impart interactive experiences for hands-on learning in engineering laboratories. The ARCore technology enables a smartphone to sense its environment and detect horizontal and vertical surfaces, thus allowing the smartphone to estimate any position in its workspace. In this mobile app, with touch-based interaction and AR feedback, the user can interact with a wheeled mobile robot and reinforce the concepts of kinematics for a differential drive mobile robot. The user experience is evaluated and system performance is validated through a user study with participants. The assessment shows that the proposed AR interface for interacting with the experimental setup is intuitive, easy to use, exciting, and recommendable.

In this paper, the axial symmetry is used to analyze the deformation and stress change of the wheel, so as to reduce the scale of analysis and reduce the cost in industrial production. Firstly, the material properties are defined, then the rotation section of the wheel is established, the boundary conditions are defined, the model is divided by finite element, the angular velocity and pressure load during rotation are applied, and the radial and axial deformation diagram, radial, axial and equivalent stress distribution diagram of the wheel are obtained through analysis and solution. The use of axisymmetric characteristics can reduce the analysis cost in the analysis, and can be applied to materials or components with such characteristics, so as to facilitate the design and improvement of products and reduce the production cost.

Embedded systems often consist of deeply intertwined hardware and software components. At the same time, they are often used in safety-critical applications, where an error may result in enormous costs or even loss of human lives. Existing verification techniques that show the absence of errors do not scale well for complex integrated HW/SW systems. In this paper, we present a dependence analysis and automated partitioning approach for the formal analysis of HW/SW codesigns that are modeled in SystemC. The key idea of our approach is threefold: first, we partition a given system into loosely coupled submodels. Second, we analyze the dependences between these submodels and compute an abstract verification interface for each of them, which captures all possible influences of all other submodels. Third, we verify global properties of the overall system by verifying them separately for each subsystem. We demonstrate that our approach significantly reduces verification times and increases scalability with results for an anti-lock braking system.

Software development for Cyber-Physical Systems (CPS), e.g., autonomous vehicles, requires both functional and non-functional quality assurance to guarantee that the CPS operates safely and effectively. EAST-ADL is a domain specific architectural language dedicated to safety-critical automotive embedded system design. We have previously modified EAST-ADL to include energy constraints and transformed energy-aware real-time (ERT) behaviors modeled in EAST-ADL/Stateflow into UPPAAL models amenable to formal verification. Previous work is extended in this paper by including support for Simulink and an integration of Simulink/Stateflow (S/S) within the same too lchain. S/S models are transformed, based on the extended ERT constraints with probability parameters, into verifiable UPPAAL-SMC models and integrate the translation with formal statistical analysis techniques: Probabilistic extension of EAST-ADL constraints is defined as a semantics denotation. A set of mapping rules is proposed to facilitate the guarantee of translation. Formal analysis on both functional- and non-functional properties is performed using Simulink Design Verifier and UPPAAL-SMC. Our approach is demonstrated on the autonomous traffic sign recognition vehicle case study.

Several applications adopt electromagnetic sensors, that base their principle on the presence of magnets realized with specific magnetic materials that show a rather high remanence, but low coercivity. This work concerns the production, analysis and characterization of hybrid composite materials, with the use of metal powders, which aim to reach those specific properties. In order to obtain the best coercivity and remanence characteristics various "recipes" have been used with different percentages of soft and hard magnetic materials, bonded together by a plastic binder. The goal was to find out the interdependence between the magnetic powder composition and the characteristics of the final material. Soft magnetic material (special Fe powder) has been used to obtain a low coercivity value, while hard materials were primarily used for maintaining a good induction remanence; by increasing the soft proportion a higher magnetic permeability has been also obtained. All the selected materials have been characterized and then tested; in order to verify the validity of the proposed materials two practical tests have been performed. Special magnets have been realized for a comparison with original ones (AlNiCo and ferrite) for two experimental cases: the first is consisting in an encoder realized through a toothed wheel, the second regards the special system used for the electric guitars.

With the application and promotion of electric vehicles, vehicle security problems caused by actuator reliability have become increasingly prominent. Firstly, the paper analyses and sums motor failure modes and their effects of permanent magnet synchronous motor (PMSM) , which is commonly used on electric vehicles. And then design a hierarchical structure of the vehicle control strategies and the corresponding algorithms, and adjust based on the different failure modes. Finally conduct simulation conditions in CarSim environment. Verify the control strategy and algorithm can maintain vehicle stability and reduce the burden on driver under motor failure conditions.