The Experts below are selected from a list of 415131 Experts worldwide ranked by ideXlab platform

Sabine Glesner - One of the best experts on this subject based on the ideXlab platform.

  • IESS - Timed Path Conditions in MATLAB/Simulink
    System Level Design from HW SW to Memory for Embedded Systems, 2017
    Co-Authors: Marcus Mikulcak, Paula Herber, Thomas Göthel, Sabine Glesner
    Abstract:

    MATLAB/Simulink is a widely-used industrial tool for the development of complex embedded systems. However, due to the complexity and the dynamic character of the developed models, their analysis is a difficult challenge, in particular if timing aspects are involved. In this paper, we present an approach for the construction of timed path conditions for MATLAB/Simulink models. Timed path conditions allow for fine-grained conclusions about the existence of possibly critical paths through a model containing time-dependent elements. With the help of timed path conditions, it is possible to identify interference and non-interference between model parts. Furthermore, they have the potential to reduce the complexity of models to improve verifiability, reason about compliance with security policies as well as generate feasible, efficient test cases. We demonstrate the applicability of our approach with a shared buffer for public as well as confidential data.

  • Timed Path Conditions in MATLAB/Simulink
    2015
    Co-Authors: Marcus Mikulcak, Paula Herber, Thomas Göthel, Sabine Glesner
    Abstract:

    MATLAB/Simulink is a widely-used industrial tool for the development of complex embedded systems. However, due to the complexity and the dynamic character of the developed models, their analysis is a difficult challenge, in particular if timing aspects are involved. In this paper, we present an approach for the construction of timed path conditions for MATLAB/Simulink models. Timed path conditions allow for fine-grained conclusions about the existence of possibly critical paths through a model containing time-dependent elements. With the help of timed path conditions, it is possible to identify interference and non-interference between model parts. Furthermore, they have the potential to reduce the complexity of models to improve verifiability, reason about compliance with security policies as well as generate feasible, efficient test cases. We demonstrate the applicability of our approach with a shared buffer for public as well as confidential data.

  • SEFM - Formal Verification of Discrete-Time MATLAB/Simulink Models Using Boogie
    Software Engineering and Formal Methods, 2014
    Co-Authors: Robert Reicherdt, Sabine Glesner
    Abstract:

    Matlab/Simulink is a widely used industrial tool for the development of embedded systems. Many of these systems are safety critical, especially in automotive industries. At the same time, automatic formal verification techniques for Simulink, in particular on model level, are rare and often suffer from scalability issues. In this paper, we present an automatic transformation of discrete-time Matlab/Simulink models into the intermediate verification language Boogie. This transformation enables us to use the Boogie verification framework and inductive invariant checking for the automatic formal verification of Matlab/Simulink models. Additionally, verification objectives for common error classes are generated automatically. With our approach, we provide an automatic formal verification technique for Matlab/Simulink and the most common error classes which scales better than existing techniques in many cases. To demonstrate the practical applicability, we have applied our approach to a number of case studies from the automotive domain.

  • Slicing MATLAB simulink models
    Proceedings - International Conference on Software Engineering, 2012
    Co-Authors: Robert Reicherdt, Sabine Glesner
    Abstract:

    MATLAB Simulink is the most widely used industrial tool for developing complex embedded systems in the automotive sector. The resulting Simulink models often consist of more than ten thousand blocks and a large number of hierarchy levels. To ensure the quality of such models, automated static analyses and slicing are necessary to cope with this complexity. In particular, static analyses are required that operate directly on the models. In this article, we present an approach for slicing Simulink Models using dependence graphs and demonstrate its efficiency using case studies from the automotive and avionics domain. With slicing, the complexity of a model can be reduced for a given point of interest by removing unrelated model elements, thus paving the way for subsequent static quality assurance methods.

  • ICSE - Slicing MATLAB simulink models
    2012 34th International Conference on Software Engineering (ICSE), 2012
    Co-Authors: Robert Reicherdt, Sabine Glesner
    Abstract:

    MATLAB Simulink is the most widely used industrial tool for developing complex embedded systems in the automotive sector. The resulting Simulink models often consist of more than ten thousand blocks and a large number of hierarchy levels. To ensure the quality of such models, automated static analyses and slicing are necessary to cope with this complexity. In particular, static analyses are required that operate directly on the models. In this article, we present an approach for slicing Simulink Models using dependence graphs and demonstrate its efficiency using case studies from the automotive and avionics domain. With slicing, the complexity of a model can be reduced for a given point of interest by removing unrelated model elements, thus paving the way for subsequent static quality assurance methods.

Takuya Azumi - One of the best experts on this subject based on the ideXlab platform.

  • ISORC - MATLAB/Simulink Benchmark Suite for ROS-based Self-driving Software Platform
    2019 IEEE 22nd International Symposium on Real-Time Distributed Computing (ISORC), 2019
    Co-Authors: Shota Tokunaga, Keita Miura, Takuya Azumi
    Abstract:

    In recent years, self-driving systems have been developed worldwide, and the technology has been making remarkable progress. One approach to the development of the autonomous vehicle is using ROS which is an open-source middleware framework used for developing robot applications. On the other hand, the popular approach in the automotive industry is using MATLAB/Simulink which is the software for modeling, simulating, and analyzing. MATLAB/Simulink has an interface connecting ROS and MATLAB/Simulink. However, it is not used much in the development of self-driving systems because there are not enough samples for the self-driving systems. Therefore, we provide a MATLAB/Simulink benchmark suite for a ROS-based self-driving system called Autoware. Autoware provides an abundant set of self-driving modules and enables to simulate and operate the autonomous vehicle. The provided benchmark is a set of MATLAB code and Simulink model samples. They assist to design the self-driving systems using MATLAB/Simulink.

  • ICCPS - MATLAB/Simulink benchmark suite for ROS-based self-driving system: demo abstract
    Proceedings of the 10th ACM IEEE International Conference on Cyber-Physical Systems - ICCPS '19, 2019
    Co-Authors: Shota Tokunaga, Noriyuki Ota, Yoshiharu Tange, Keita Miura, Takuya Azumi
    Abstract:

    This paper proposes a MATLAB/Simulink benchmark suite for an open-source self-driving system based on Robot Operating System (ROS). In recent years, self-driving systems have been developed around the world. One approach to the development of self-driving systems is the utilization of ROS which is an open-source middleware framework used in the development of robot applications. On the other hand, the popular approach in the automotive industry is the utilization of MATLAB/Simulink which is software for modeling, simulating, and analyzing. MATLAB/Simulink provides an interface between ROS and MATLAB/Simulink that enables to create functionalities of ROS-based robots in MATLAB/Simulink. However, it is not been fully utilized in the development of self-driving systems yet because there are not enough samples for self-driving, and it is difficult for developers to adopt co-development. Therefore, we provide a MATLAB/Simulink benchmark suite for a ROS-based self-driving system called Autoware. Autoware is popular open-source software that provides a complete set of self-driving modules. The provided benchmark contains MATLAB/Simulink samples available in Autoware. They help to design ROS-based self-driving systems using MATLAB/Simulink.

  • RSP - Autoware Toolbox: MATLAB/Simulink Benchmark Suite for ROS-based Self-driving Software Platform
    Proceedings of the 30th International Workshop on Rapid System Prototyping (RSP'19) - RSP '19, 2019
    Co-Authors: Keita Miura, Shota Tokunaga, Noriyuki Ota, Yoshiharu Tange, Takuya Azumi
    Abstract:

    This paper describes a MATLAB/Simulink benchmark suite for an open-source self-driving system based on Robot Operating System (ROS). In recent years, self-driving systems have been developed worldwide, and the technology has been making remarkable progress. One approach to the development of the self-driving systems is the utilization of ROS which is an open-source middleware framework used for developing robot applications. On the other hand, the popular approach in the automotive industry is the utilization of MATLAB/Simulink which is the software for modeling, simulating, and analyzing. MATLAB/Simulink provides an interface between ROS and MATLAB/Simulink that enables to create functionalities of ROS-based robots in MATLAB/Simulink. However, it has not been fully utilized in the development of the self-driving systems yet because there are not enough open-source models for self-driving. Thus the co-development is difficult. Therefore, we provide a MATLAB/Simulink benchmark suite for a ROS-based self-driving system called Autoware. Autoware is popular open-source software that provides a complete set of self-driving modules. The provided benchmark contains MATLAB/Simulink models. They help to design the ROS-based self-driving systems using MATLAB/Simulink. Moreover, we investigated other benchmarks for self-driving and indicated that this is the first work aiming to the ROS-based self-driving systems with MATLAB/Simulink.

Kodjo Agbossou - One of the best experts on this subject based on the ideXlab platform.

  • interface design and software development for pem fuel cell modeling based on matlab simulink environment
    WRI World Congress on Software Engineering, 2009
    Co-Authors: Yancheng Xiao, Kodjo Agbossou
    Abstract:

    This paper is dealing with the interface design and software development for proton exchange membrane (PEM) fuel cell modeling based on Matlab/Simulink environment. Three models used in the software, steady-state mode, dynamic model and thermodynamic model, are described first. These models are then implemented through the graphic user interface (GUI) programming by Simulink, and the simulation results are visualized. There are voltage overshoots/ undershoots appearing in the results, which is come from the combination of electrical dynamic model and thermodynamic model. For the interface design and software development, a GUI file(*.fig) is designed in Matlab interactively, a main program (*.m) is coded using Matlab language, and a Simulink model (*.mdl) is designed based on the fuel cell model in the work. The Matlab main program calls Matlab GUI file and Simulink diagram to complete the fuel cell simulation. The software are applied to PEM fuel cell and solid oxide fuel cell (SOFC) successfully.

  • Interface Design and Software Development for PEM Fuel Cell Modeling Based on Matlab/Simulink Environment
    2009 WRI World Congress on Software Engineering, 2009
    Co-Authors: Yancheng Xiao, Kodjo Agbossou
    Abstract:

    This paper is dealing with the interface design and software development for proton exchange membrane (PEM) fuel cell modeling based on Matlab/Simulink environment. Three models used in the software, steady-state mode, dynamic model and thermodynamic model, are described first. These models are then implemented through the graphic user interface (GUI) programming by Simulink, and the simulation results are visualized. There are voltage overshoots/ undershoots appearing in the results, which is come from the combination of electrical dynamic model and thermodynamic model. For the interface design and software development, a GUI file(*.fig) is designed in Matlab interactively, a main program (*.m) is coded using Matlab language, and a Simulink model (*.mdl) is designed based on the fuel cell model in the work. The Matlab main program calls Matlab GUI file and Simulink diagram to complete the fuel cell simulation. The software are applied to PEM fuel cell and solid oxide fuel cell (SOFC) successfully.

Yao Shouguang - One of the best experts on this subject based on the ideXlab platform.

Shota Tokunaga - One of the best experts on this subject based on the ideXlab platform.

  • ISORC - MATLAB/Simulink Benchmark Suite for ROS-based Self-driving Software Platform
    2019 IEEE 22nd International Symposium on Real-Time Distributed Computing (ISORC), 2019
    Co-Authors: Shota Tokunaga, Keita Miura, Takuya Azumi
    Abstract:

    In recent years, self-driving systems have been developed worldwide, and the technology has been making remarkable progress. One approach to the development of the autonomous vehicle is using ROS which is an open-source middleware framework used for developing robot applications. On the other hand, the popular approach in the automotive industry is using MATLAB/Simulink which is the software for modeling, simulating, and analyzing. MATLAB/Simulink has an interface connecting ROS and MATLAB/Simulink. However, it is not used much in the development of self-driving systems because there are not enough samples for the self-driving systems. Therefore, we provide a MATLAB/Simulink benchmark suite for a ROS-based self-driving system called Autoware. Autoware provides an abundant set of self-driving modules and enables to simulate and operate the autonomous vehicle. The provided benchmark is a set of MATLAB code and Simulink model samples. They assist to design the self-driving systems using MATLAB/Simulink.

  • ICCPS - MATLAB/Simulink benchmark suite for ROS-based self-driving system: demo abstract
    Proceedings of the 10th ACM IEEE International Conference on Cyber-Physical Systems - ICCPS '19, 2019
    Co-Authors: Shota Tokunaga, Noriyuki Ota, Yoshiharu Tange, Keita Miura, Takuya Azumi
    Abstract:

    This paper proposes a MATLAB/Simulink benchmark suite for an open-source self-driving system based on Robot Operating System (ROS). In recent years, self-driving systems have been developed around the world. One approach to the development of self-driving systems is the utilization of ROS which is an open-source middleware framework used in the development of robot applications. On the other hand, the popular approach in the automotive industry is the utilization of MATLAB/Simulink which is software for modeling, simulating, and analyzing. MATLAB/Simulink provides an interface between ROS and MATLAB/Simulink that enables to create functionalities of ROS-based robots in MATLAB/Simulink. However, it is not been fully utilized in the development of self-driving systems yet because there are not enough samples for self-driving, and it is difficult for developers to adopt co-development. Therefore, we provide a MATLAB/Simulink benchmark suite for a ROS-based self-driving system called Autoware. Autoware is popular open-source software that provides a complete set of self-driving modules. The provided benchmark contains MATLAB/Simulink samples available in Autoware. They help to design ROS-based self-driving systems using MATLAB/Simulink.

  • RSP - Autoware Toolbox: MATLAB/Simulink Benchmark Suite for ROS-based Self-driving Software Platform
    Proceedings of the 30th International Workshop on Rapid System Prototyping (RSP'19) - RSP '19, 2019
    Co-Authors: Keita Miura, Shota Tokunaga, Noriyuki Ota, Yoshiharu Tange, Takuya Azumi
    Abstract:

    This paper describes a MATLAB/Simulink benchmark suite for an open-source self-driving system based on Robot Operating System (ROS). In recent years, self-driving systems have been developed worldwide, and the technology has been making remarkable progress. One approach to the development of the self-driving systems is the utilization of ROS which is an open-source middleware framework used for developing robot applications. On the other hand, the popular approach in the automotive industry is the utilization of MATLAB/Simulink which is the software for modeling, simulating, and analyzing. MATLAB/Simulink provides an interface between ROS and MATLAB/Simulink that enables to create functionalities of ROS-based robots in MATLAB/Simulink. However, it has not been fully utilized in the development of the self-driving systems yet because there are not enough open-source models for self-driving. Thus the co-development is difficult. Therefore, we provide a MATLAB/Simulink benchmark suite for a ROS-based self-driving system called Autoware. Autoware is popular open-source software that provides a complete set of self-driving modules. The provided benchmark contains MATLAB/Simulink models. They help to design the ROS-based self-driving systems using MATLAB/Simulink. Moreover, we investigated other benchmarks for self-driving and indicated that this is the first work aiming to the ROS-based self-driving systems with MATLAB/Simulink.

  • RTAS - Demo Abstract: Co-simulation Framework for Autonomous Driving Systems with MATLAB/Simulink
    2017 IEEE Real-Time and Embedded Technology and Applications Symposium (RTAS), 2017
    Co-Authors: Shota Tokunaga, Takuya Azumi
    Abstract:

    Autonomous driving vehicles are currently being developed in many countries. Autonomous driving systems are developed using the Robot Operating System (ROS), which is suitable for the development of robotics and used for various systems of autonomous driving vehicles. However, in the automotive industry, these systems have often been designed using MATLAB/Simulink, can simulate and evaluate models created for autonomous driving. These models cannot be used with the systems based on ROS. To use a model created using MATLAB/Simulink in ROS, it is necessary to rewrite the model for ROS and incorporate it into the autonomous driving system, reducing development efficiency. Therefore, we propose an integrated development framework that can simulate and operate an autonomous driving system based on ROS with MATLAB/Simulink. The proposed framework improves the development efficiency because the model created by MATLAB/Simulink can be used in the systems without a separate incorporation step. In this demonstration, we perform a co-simulation with the autonomous driving system using the proposed framework.