scholarly journals Formally-based Model-Driven Development of Collaborative Robotic Applications

2021 ◽  
Vol 102 (3) ◽  
Author(s):  
Mehrnoosh Askarpour ◽  
Livia Lestingi ◽  
Samuele Longoni ◽  
Niccolò Iannacci ◽  
Matteo Rossi ◽  
...  
Keyword(s):  
Human Behavior ◽  
Development Process ◽  
Model Design ◽  
Realistic Case ◽  
Safety Requirements ◽  
Model Driven ◽  
Model Based ◽  
Uml Profiles ◽  
Safety Considerations ◽  
Robotic Applications

AbstractThe development of Human Robot Collaborative (HRC) systems faces many challenges. First, HRC systems should be adaptable and re-configurable to support fast production changes. However, in the development of HRC applications safety considerations are of paramount importance, as much as classical activities such as task programming and deployment. Hence, the reconfiguration and reprogramming of executing tasks might be necessary also to fulfill the desired safety requirements. Model-based software engineering is a suitable means for agile task programming and reconfiguration. We propose a model-based design-to-deployment toolchain that simplifies the routine of updating or modifying tasks. This toolchain relies on (i) UML profiles for quick model design, (ii) formal verification for exhaustive search for unsafe situations (caused by intended or unintended human behavior) within the model, and (iii) trans-coding tools for automating the development process. The toolchain has been evaluated on a few realistic case studies. In this paper, we show a couple of them to illustrate the applicability of the approach.

scholarly journals Using Model-Driven Risk Analysis in Component-Based Development

2012 ◽  
pp. 330-380 ◽  
Author(s):  
Gyrd Brændeland ◽  
Ketil Stølen
Keyword(s):  
Risk Analysis ◽  
Development Process ◽  
System Development ◽  
Component Composition ◽  
Modular System ◽  
Analysis Method ◽  
Model Driven ◽  
Model Based ◽  
Component Based Development ◽  
Analysis Methods

Modular system development causes challenges for security and safety as upgraded sub-components may interact with the system in unforeseen ways. Due to their lack of modularity, conventional risk analysis methods are poorly suited to address these challenges. We propose to adjust an existing method for model-based risk analysis into a method for component-based risk analysis. We also propose a stepwise integration of the component-based risk analysis method into a component-based development process. By using the same kinds of description techniques to specify functional behaviour and risks, we may achieve upgrading of risk analysis documentation as an integrated part of component composition and refinement.

Introducing Safety Requirements Traceability Support in Model-Driven Development of Robotic Applications

2011 ◽  
Vol 60 (8) ◽  
pp. 1059-1071 ◽  
Author(s):  
Pedro Sanchez ◽  
Diego Alonso ◽  
Francisca Rosique ◽  
Barbara Alvarez ◽  
Juan A. Pastor
Keyword(s):  
Requirements Traceability ◽  
Model Driven Development ◽  
Safety Requirements ◽  
Model Driven ◽  
Robotic Applications

scholarly journals The New Trend of State Estimation: From Model-Driven to Hybrid-Driven Methods

Sensors ◽  
2021 ◽  
Vol 21 (6) ◽  
pp. 2085
Author(s):  
Xue-Bo Jin ◽  
Ruben Jonhson Robert RobertJeremiah ◽  
Ting-Li Su ◽  
Yu-Ting Bai ◽  
Jian-Lei Kong
Keyword(s):  
Kalman Filter ◽  
State Estimation ◽  
Future Development ◽  
Data Driven ◽  
Estimation Methods ◽  
Multiple Model ◽  
Development Trends ◽  
Research Results ◽  
Model Driven ◽  
Model Based

State estimation is widely used in various automated systems, including IoT systems, unmanned systems, robots, etc. In traditional state estimation, measurement data are instantaneous and processed in real time. With modern systems’ development, sensors can obtain more and more signals and store them. Therefore, how to use these measurement big data to improve the performance of state estimation has become a hot research issue in this field. This paper reviews the development of state estimation and future development trends. First, we review the model-based state estimation methods, including the Kalman filter, such as the extended Kalman filter (EKF), unscented Kalman filter (UKF), cubature Kalman filter (CKF), etc. Particle filters and Gaussian mixture filters that can handle mixed Gaussian noise are discussed, too. These methods have high requirements for models, while it is not easy to obtain accurate system models in practice. The emergence of robust filters, the interacting multiple model (IMM), and adaptive filters are also mentioned here. Secondly, the current research status of data-driven state estimation methods is introduced based on network learning. Finally, the main research results for hybrid filters obtained in recent years are summarized and discussed, which combine model-based methods and data-driven methods. This paper is based on state estimation research results and provides a more detailed overview of model-driven, data-driven, and hybrid-driven approaches. The main algorithm of each method is provided so that beginners can have a clearer understanding. Additionally, it discusses the future development trends for researchers in state estimation.

scholarly journals USING MODEL-BASED SYSTEMS ENGINEERING FOR NEED-BASED AND CONSISTENT SUPPORT OF THE DESIGN PROCESS

2021 ◽  
Vol 1 ◽  
pp. 3369-3378
Author(s):  
Stephan Husung ◽  
Christian Weber ◽  
Atif Mahboob ◽  
Sven Kleiner
Keyword(s):  
Systems Engineering ◽  
Development Process ◽  
Added Value ◽  
System Level ◽  
System Failure ◽  
Model Based ◽  
Continuous Use ◽  
Model Based Systems Engineering ◽  
Consistent Support ◽  
Modelling Approaches

AbstractModel-Based Systems Engineering (MBSE) is an efficient approach to support product development in order to meet today's challenges. The MBSE approach includes methods and, above all, modelling approaches of the technical system with the aim of continuous use in development. The objective of this paper is to use the potential of the MBSE models and to show the added value of such models on the system level when used as a single source. With this objective, this paper presents a three-step approach to systematically identify and apply meaningful modelling approaches within MBSE, based on the needs during the development process. Furthermore, an FMEA example is included in this paper to elaborate the use of MBSE in the system failure analysis.

scholarly journals Collaborative Modeling of Group Learning Applications Using Eclipse Technology

Proceedings ◽  
2019 ◽  
Vol 31 (1) ◽  
pp. 21
Author(s):  
Yoel Arroyo ◽  
Ana I. Molina ◽  
Miguel A. Redondo ◽  
Jesús Gallardo ◽  
Carmen Lacave
Keyword(s):  
Development Process ◽  
Group Learning ◽  
Complex Task ◽  
Learning Collaborative ◽  
Interactive Applications ◽  
Model Driven ◽  
Collaborative Modeling ◽  
Innovative Model ◽  
Software Engineers ◽  
Computer Aided Software Engineering

The design and creation of groupware tools is a complex task that usually requires the participation of different stakeholders (software engineers, designers, etc.), either working at the same time or collaborating asynchronously. This paper describes an innovative model-driven development process to support the collaborative modeling of group learning applications, as well as the Computer Aided Software Engineering (CASE) tool that technologically supports it, the Learning Collaborative Interactive Applications Tool (Learn-CIAT) graphical editor. In its development, we applied technologies integrated within the Eclipse platform. The processes and tools described in this paper supply an important contribution to systematize the design and development of these kinds of applications.

Verwendung von Zusicherungen in einem modellbasierten Entwicklungsprozess (Using Assertions and Watchdogs in a Model-Based Development Process)

2002 ◽  
Vol 44 (3) ◽  
Author(s):  
Andreas Rau
Keyword(s):  
Development Process ◽  
Model Based

Die Automobilindustrie ist momentan im Begriff, einen neuen Ansatz für die Entwicklung eingebetteter Systeme zu übernehmen. Dieser Ansatz basiert auf neuen Modellierungs- und Simulationswerkzeugen, die einen nahtlosen Prozess von der ersten Idee bis zur Serie durch schrittweise Verfeinerung eines Modells und Implementierung mittels automatischer Codegenerierung versprechen. Jedoch müssen einige Details dieses Prozesses erst noch definiert werden. Dabei sollten Erfahrungen und erprobte Techniken aus traditionellen Softwareentwicklungsprozessen berücksichtigt werden. Zum Beispiel kann durch Zusicherungen das Modell abgesichert und seine Tiefe und Qualität verbessert werden. Solche Prüfungen können sowohl in der Simulation als auch zur Codegenerierung für die Zielumgebung verwendet werden. Dies führt zu einer erhöhten Zuverlässigkeit des Endprodukts und stellt au3erdem eine Grobverifikation des verwendeten Codegenerators dar. Der vorliegende Artikel beschreibt Konzept und Anforderungen für solche modellbasierten Prüfungen und ihren praktischen Einsatz mit SIMULINK-Modellen.

scholarly journals The Design of an Instructional Model Based on Connectivism and Constructivism to Create Innovation in Real World Experience

2018 ◽  
Vol 11 (3) ◽  
pp. 12 ◽  
Author(s):  
Kanokrat Jirasatjanukul ◽  
Namon Jeerungsuwan
Keyword(s):  
Real World ◽  
Model Evaluation ◽  
Sampling Technique ◽  
Instructional Model ◽  
Model Design ◽  
Research Results ◽  
Purposive Sampling ◽  
Evaluation Form ◽  
Model Based ◽  
High Level

The objectives of the research were to (1) design an instructional model based on Connectivism and Constructivism to create innovation in real world experience, (2) assess the model designed–the designed instructional model. The research involved 2 stages: (1) the instructional model design and (2) the instructional model rating. The sample consisted of 7 experts, and the Purposive Sampling Technique was used. The research instruments were the instructional model and the instructional model evaluation form. The statistics used in the research were means and standard division. The research results were (1) the Instructional Model based on Connectivism and Constructivism to Create innovation in Real World Experience consisted of 3 components. These were Connectivism, Constructivism and Innovation in Real World Experience and (2) the instructional model rating was at a high level (=4.37, S.D.=0.41). The research results revealed that the Instructional Model Based on Connectivism and Constructivism to Create Innovation in Real World Experience was a model that can be used in learning, in that it promoted the creation of real world experience innovation.

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