RobotML for industrial robots: Design and simulation of manipulation scenarios

Kchir, Selma; Dhouib, Saadia; Tatibouet, Jérémie; Gradoussoff, Baptiste; Simoes, Max Da Silva

doi:10.1109/etfa.2016.7733727

Cited by 5 publications

(4 citation statements)

References 6 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…We used those features to compare EARL to the other MDSD languages. The assessment is based on the papers describing the MDSD languages, i.e., RobotML [5,6], BCM (BRICS) [1,2], SmartSoft [8], V3CMM [10] as well as the internet page of the SmartSoft project [61]. The results of the comparison are presented in the form of Table 9, please see the following.…”

Section: Discussionmentioning

confidence: 99%

See 1 more Smart Citation

EARL—Embodied Agent-Based Robot Control Systems Modelling Language

et al. 2020

View full text Add to dashboard Cite

The paper presents the Embodied Agent-based Robot control system modelling Language (EARL). EARL follows a Model-Driven Software Development approach (MDSD), which facilitates robot control system development. It is based on a mathematical method of robot controller specification, employing the concept of an Embodied Agent, and a graphical modelling language: System Modelling Language (SysML). It combines the ease of use of SysML with the precision of mathematical specification of certain aspects of the designed system. It makes the whole system specification effective, from the point of view of the time needed to create it, conciseness of the specification and the possibility of its analysis. By using EARL it is possible to specify systems both with fixed and variable structure. This was achieved by introducing a generalised system model and presenting particular structures of the system in terms of modelling block configurations adapted by using instances. FABRIC framework was created to support the implementation of EARL-based controllers. EARL is compatible with component based robotic middlewares (e.g., ROS and Orocos).

show abstract

Section: Discussionmentioning

confidence: 99%

“…RobotML [5,6] is used to define a metamodel expressed in UML [7]. The model of the designed system is decomposed into components such as sensors, effectors, maps or planners.…”

Section: Mdsd In Roboticsmentioning

confidence: 99%

EARL—Embodied Agent-Based Robot Control Systems Modelling Language

et al. 2020

View full text Add to dashboard Cite

show abstract

“…RobotML [38] is a dedicated language for designing industrial robotic applications, developed as a Papyrus project that uses UML profiles as the metamodeling language. In other words, RobotML is a domain-specific language based on UML.…”

Section: The Robotml Modeling Language For Robotic Systemsmentioning

confidence: 99%

Incorporating measurement uncertainty into OCL/UML primitive datatypes

et al. 2019

View full text Add to dashboard Cite

The correct representation of the relevant properties of a system is an essential requirement for the effective use and wide adoption of model-based practices in industry. Uncertainty is one of the inherent properties of any measurement or estimation that is obtained in any physical setting; as such, it must be considered when modeling software systems that deal with real data. Although a few modeling languages enable the representation of measurement uncertainty, these aspects are not normally incorporated into their type systems. Therefore, operating with uncertain values and propagating their uncertainty become cumbersome processes, which hinder their realization in real environments. This paper proposes an extension of OCL/UML primitive datatypes that enables the representation of the uncertainty that comes from physical measurements or user estimates into the models, together with an algebra of operations that are defined for the values of these types.

show abstract

“…Case 2. For a second language we chose RobotML [44], a dedicated language for designing robotic applications. It permits both simulation and deployment to multi-target platforms.…”

Section: Applicability (Rq2) Effectiveness (Rq3) and Efficiency (Rq4)mentioning

confidence: 99%

Specifying quantities in software models

Burgueño

Mayerhofer

Wimmer

et al. 2019

Information and Software Technology

View full text Add to dashboard Cite

Context: An essential requirement for the design and development of any engineering application that deals with realworld physical systems is the formal representation and processing of physical quantities, comprising both measurement uncertainty and units. Although solutions exist for several programming languages and simulation frameworks, this problem has not yet been fully solved for software models. Objective: This paper shows how both measurement uncertainty and units can be effectively incorporated into software models, becoming part of their basic type systems. Method: We introduce the main concepts and mechanisms needed for representing and handling physical quantities in software models. More precisely, we describe an extension of basic type Real, called Quantity, and a set of operations defined for the values of that type, together with a ready-to-use library of dimensions and units, which can be added to any modeling project. Results: We show how our approach permits modelers to safely represent and operate with physical quantities, statically ensuring type-and unit-safe assignments and operations, prior to any simulation of the system or implementation in any programming language. Conclusion: Our approach improves the expressiveness and type-safety of software models with respect to measurement uncertainty and units of physical quantities, and its effective use in modeling projects of physical systems.

show abstract

RobotML for industrial robots: Design and simulation of manipulation scenarios

Cited by 5 publications

References 6 publications

EARL—Embodied Agent-Based Robot Control Systems Modelling Language

EARL—Embodied Agent-Based Robot Control Systems Modelling Language

Incorporating measurement uncertainty into OCL/UML primitive datatypes

Specifying quantities in software models

Contact Info

Product

Resources

About