Engineering Robotics Software Architectures with Exchangeable Model Transformations

Adam, Kai; Hölldobler, Katrin; Rumpe, Bernhard; Wortmann, Andreas

doi:10.1109/irc.2017.16

Cited by 8 publications

(8 citation statements)

References 15 publications

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“…A survey on safety-critical robotics [82] identified seven focus areas for the development of robots that can safely work alongside humans and other robots, in unstructured environments. These areas are: (1) modelling and simulation of the physical environment to enable better safety analysis, (2) formal verification of robot systems, (3) controllers that are correct-by-construction, (4) identification and monitoring of hazardous situations, (5) models of human-robot interaction, (6) online safety monitoring that adapts to the robot's context, and (7) certification evidence. In contrast, our survey focusses on the application of formal methods to any type of autonomous robotic system.…”

Section: Related Workmentioning

confidence: 99%

“…The BRICS Component Model [38] translates high-level models into platform-specific componentmodels for Orocos and ROS. Another model-driven approach is the MontiArcAutomaton architecture description language [145] which translates models into program code, mostly for ROS [3]. Performance Level Profiles [33] is an XML-based language for describing the expected properties of functional modules.…”

Section: General Software Engineering Techniques For Robotic Systemsmentioning

confidence: 99%

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Formal Specification and Verification of Autonomous Robotic Systems

et al. 2019

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Autonomous robotic systems are complex, hybrid, and often safety-critical; this makes their formal specification and verification uniquely challenging. Though commonly used, testing and simulation alone are insufficient to ensure the correctness of, or provide sufficient evidence for the certification of, autonomous robotics. Formal methods for autonomous robotics has received some attention in the literature, but no resource provides a current overview. This paper systematically surveys the state-of-the-art in formal specification and verification for autonomous robotics. Specially, it identifies and categorises the challenges posed by, the formalisms aimed at, and the formal approaches for the specification and verification of autonomous robotics. Introduction, Methodology and Related WorkAn autonomous system is an artificially intelligent entity that makes decisions in response to input, independent of human interaction. Robotic systems are physical entities that interact with the physical world. Thus, we consider an autonomous robotic system as a machine that uses Artificial Intelligence (AI), has a physical presence in and interacts with the real world. They are complex, inherently hybrid, systems, combining both hardware and software; they often require close safety, legal, and ethical consideration. Autonomous robotics are increasingly being used in commonplace-scenarios, such as driverless cars [68], pilotless aircraft [176], and domestic assistants [174,60].While for many engineered systems, testing, either through real deployment or via simulation, is deemed sufficient; the unique challenges of autonomous robotics, their dependence on sophisticated software control and decision-making, and their increasing deployment in safety-critical scenarios, require a stronger form of verification. This leads us towards using formal methods, which are mathematically-based techniques for the specification and verification of software systems, to ensure the correctness of, and provide sufficient evidence for the certification of, robotic systems.We contribute an overview and analysis of the state-of-the-art in formal specification and verification of autonomous robotics. §1.1 outlines the scope, research questions and search criteria for our survey. §1.2 describes related work concerning formal methods for robotics and differentiates them from our work. We recognise the important role that middleware architectures and, non-and semi-formal techniques have in the development of reliable robotics and we briefly summarise some of these techniques in §2. The specification and verification challenges raised by autonomous robotic systems are discussed next: §3 describes the challenges of their context (the external challenges) and §4 describes the challenges of their organisation (the internal challenges). §5 discusses the formalisms used in the literature for specification and verification of autonomous robotics. §6 characterises the approaches to formal specification and verification of autonomous robotics found in the li...

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Section: Related Workmentioning

confidence: 99%

Section: General Software Engineering Techniques For Robotic Systemsmentioning

confidence: 99%

Formal Specification and Verification of Autonomous Robotic Systems

et al. 2019

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“…Moreover, Mon-tiCore offers a runtime environment (RTE) providing functions and data structures which can be used by both the generated and handwritten parts of MontiCore-based tools. MontiCore has already been used to create languages and related tools in various domains including Automotive [RSW + 15], robotics [AHRW17], and cloud applications [NPR13].…”

Section: Monticorementioning

confidence: 99%

Applied Artifact-Based Analysis for Architecture Consistency Checking

Greifenberg

Hillemacher

Hölldobler

2020

Ernst Denert Award for Software Engineering 2019

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The usage of models within model-driven software development aims at facilitating complexity management of the system under development and closing the gap between the problem and the solution domain. Utilizing model-driven software development (MDD) tools for agile development can also increase the complexity within a project. The huge number of different artifacts and relations, their different kinds, and the high degree of automation hinder the understanding, maintenance, and evolution within MDD projects. A systematic approach to understand and manage MDD projects with a focus on its artifacts and corresponding relations is necessary to handle the complexity. The artifact-based analysis presented in this paper is such an approach. This paper gives an overview of different contributions of the artifact-based analysis but focuses on a specific kind of analysis: architecture consistency checking of model-driven development projects. By applying this kind of analyses, differences between the desired architecture and the actual architecture of the project at a specific point in time can be revealed.

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“…Moreover, fully automatic simulation of the cyber-physical contexts of cars and fully automatic checking of the robots behavior leads to an highly efficient development process with high quality results [BBR07]. Optimized code-generators [KRSvW18] and domain specific code generation [AHRW17b] are key for CPS. Moreover, we have extended our work from individual CPS to product lines of CPS [RSW + 15, KRR + 16, RRS + 16].…”

Section: Cps Application Domainsmentioning

confidence: 99%

“…The integration of automata and tables to model component behavior are described in [RRW13]. The integration capabilities of MontiArc have been extended and generalized in [RRRW15,AHRW17b]. For interested readers, the MontiArcAutomaton website 2 provides further information on the MontiArcAutomaton framework.…”

Section: Modeling Robotic Application Architectures and Behaviormentioning

confidence: 99%

Innovations in Model-based Software And Systems Engineering.

Hölldobler¹,

Michael²,

Ringert³

et al. 2019

JOT

Self Cite

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Engineering software and software intensive systems has become increasingly complex over the last decades. In the ongoing digitalization of all aspects of our lives in almost every domain, including, e.g., mechanical engineering, electrical engineering, medicine, entertainment, or jurisdiction, software is not only used to enable low-level controls of machines, but also to understand system conditions and optimizations potentials.To remain in control of all these heterogeneous systems of systems, a precise, but abstract understanding of these systems is necessary. To this end, models in their various forms are an important prerequisite to gain this understanding.In this article, we summarize research activities focusing on the development and use of models in software and systems engineering. This research has been carried out by the working group of Bernhard Rumpe, which started 25 years ago in Munich, continued in Braunschweig, and since 10 years carries on at RWTH Aachen University.

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Engineering Robotics Software Architectures with Exchangeable Model Transformations

Cited by 8 publications

References 15 publications

Formal Specification and Verification of Autonomous Robotic Systems

Formal Specification and Verification of Autonomous Robotic Systems

Applied Artifact-Based Analysis for Architecture Consistency Checking

Innovations in Model-based Software And Systems Engineering.

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