Modeling robot and world interfaces for reusable tasks

Heim, Robert; Nazari, Pedram Mir Seyed; Ringert, Jan Oliver; Rumpe, Bernhard; Wortmann, Andreas

doi:10.1109/iros.2015.7353610

Cited by 11 publications

(10 citation statements)

References 14 publications

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“…As a first important property of the MPC problem formulated in Section 4.1, it needs to be guaranteed that the optimization problem (6) always has a feasible solution when it is applied in closed loop (7), which is called recursive feasibility in the context of MPC [14]. Proving recursive feasibility of an MPC problem requires prior assumptions.…”

Section: Feasibility Of the Mpc Problemmentioning

confidence: 99%

“…In our case, the standing assumption is that the PN was generated with the Algorithms 1 and 2 for a manufacturing system as described in Section 2. We first show that under this assumption the MPC optimization problem (6) is feasible for every possible state of the PN, before specifically analyzing the closed loop system (7).…”

Section: Feasibility Of the Mpc Problemmentioning

confidence: 99%

“…A very promising approach to exploit these information is the concept of skill-based programming, where commands to a robot or machine are abstracted to a higher level [6,7]. It became popular in the field of robot programming, where the high level of abstraction is provided to the user in order to simplify the usage of versatile robots [8][9][10][11][12][13].…”

Section: Introductionmentioning

confidence: 99%

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Model Predictive Control for Flexible Job Shop Scheduling in Industry 4.0

Wenzelburger

Allgöwer

2021

Applied Sciences

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In the context of Industry 4.0, flexible manufacturing systems play an important role. They are designed to provide the possibility to adapt the production process by reacting to changes and enabling customer specific products. The versatility of such manufacturing systems, however, also needs to be exploited by advanced control strategies. To this end, we present a novel scheduling scheme that is able to flexibly react to changes in the manufacturing system by means of Model Predictive Control (MPC). To introduce flexibility from the start, the initial scheduling problem, which is very general and covers a variety of special cases, is formulated in a modular way. This modularity is then preserved during an automatic transformation into a Petri Net formulation, which constitutes the basis for the two presented MPC schemes. We prove that both schemes are guaranteed to complete the production problem in closed loop when reasonable assumptions are fulfilled. The advantages of the presented control framework for flexible manufacturing systems are that it covers a wide variety of scheduling problems, that it is able to exploit the available flexibility of the manufacturing system, and that it allows to prove the completion of the production problem.

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Section: Feasibility Of the Mpc Problemmentioning

confidence: 99%

Section: Feasibility Of the Mpc Problemmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Model Predictive Control for Flexible Job Shop Scheduling in Industry 4.0

Wenzelburger

Allgöwer

2021

Applied Sciences

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“…The ITS system is composed by Robots, Locations and Items as described by diagram in left of Figure 3. Robots execute tasks within a defined world [27]. It transports Items from source to target locations.…”

Section: Motivating Examplementioning

confidence: 99%

Coordination between Heterogeneous Models Using a Meta-model Composition Approach

Essadi¹,

Anwar²

2019

Adv. sci. technol. eng. syst. j.

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The technological advance as well as needs of human beings made that systems became more and more complex. In contrast, the use and creation of new modelling languages became simple and no more reserved for a handful of language experts. Consequently, many new practices of systems implementation emerged, among them, the use of different domain specific modelling languages (DSMLs) to represent the same system. Indeed, complex systems are composed by many components sometimes belonging to various domains. Thus, many teams of experts collaborate to develop such systems. Moreover, teams tend to use different DSMLs to design their concerns. This new practice generates an accidental heterogeneity due to production of various heterogeneous models representing a same system. However, those heterogeneous models need absolutely to be coordinated to facilitate communication between stakeholders and of course to ease implementation and validation of systems. This paper proposes a composition interfacebased approach to coordinate and integrate heterogeneous DSMLs in order to coordinate their models. The proposed composition interface is defined according to Bridge Design Pattern. To illustrate this approach two DSMLs are used: An Indoor Service Transport Modelling Language and an Internet of Things Modelling Language.

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“…Inspired by the iserveU service robotics research project [32], we updated the project class to feature a more realistic robotic logistics scenario using a Festo Robotino 6 robot. In the winter term of 2013/14, nine computer science master level students were assigned the task to develop a robotic logistics application that supports hospital staff (i.e., pick up and deliver items, guide and follow persons).…”

Section: B Robotino Ros Python Transport Service (C2)mentioning

confidence: 99%

Teaching agile model-driven engineering for cyber-physical systems

Ringert

Rumpe

Schulze

et al. 2017

2017 IEEE/ACM 39th International Conference on Software Engineering: Software Engineering Education and Training Track (ICSE-SE

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Abstract-Agile development methods, model-driven engineering, and cyber-physical systems are important topics in software engineering education. It is not obvious how to teach their combination while respecting individual challenges posed to students and educators. We have devised a software project class for teaching the agile MDE for CPS. The project class was held in three different semesters. In this paper, we report on the setup of our exploratory study and its goals for teaching. We base our evaluation and insights on interviews and questionnaires. Our results show the feasibility of combination of agile MDE for CPS but also the challenges this combination poses to students and educators.

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Modeling robot and world interfaces for reusable tasks

Cited by 11 publications

References 14 publications

Model Predictive Control for Flexible Job Shop Scheduling in Industry 4.0

Model Predictive Control for Flexible Job Shop Scheduling in Industry 4.0

Coordination between Heterogeneous Models Using a Meta-model Composition Approach

Teaching agile model-driven engineering for cyber-physical systems

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