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Long-term autonomy of robotic systems implicitly requires dependable platforms that are able to naturally handle hardware and software faults, problems in behaviors, or lack of knowledge. Model-based dependable platforms additionally…
In this paper we apply a model-driven engineering approach to designing domain-specific solutions for robot control system development. We present a case study of the complete process, including identification of the domain meta-model,…
Most recent software related accidents have been system accidents. To validate the absence of system hazards concerning dysfunctional interactions, industrials call for approaches of modeling system safety requirements and interaction…
Engineering the software development process in robotics is one of the basic necessities towards industrial-strength service robotic systems. A major challenge is to make the step from code-driven to model-driven systems. This is essential…
Combining component & connector architecture descriptionlanguageswithcomponentbehaviormodelinglanguages enables modeling great parts of software architectures platformindependently. Nontrivial systems typically contain components with…
We propose a component-based semantic model for Cyber-Physical Systems (CPSs) wherein the notion of a component abstracts the internal details of both cyber and physical processes, to expose a uniform semantic model of their externally…
We propose a component-based semantic model for Cyber-Physical Systems (CPSs) wherein the notion of a component abstracts the internal details of both cyber and physical processes, to expose a uniform semantic model of their externally…
Teams of heterogeneous autonomous robots become increasingly important due to their facilitation of various complex tasks. For such heterogeneous robots, there is currently no consistent way of describing the functions that each robot…
Component-based software engineering aims to reduce software development effort by reusing established components as building blocks of complex systems. Defining components in general-purpose programming languages restricts their reuse to…
Designing multi-agent robotic systems requires reasoning across tightly coupled decisions spanning heterogeneous domains, including robot design, fleet composition, and planning. Much effort has been devoted to isolated improvements in…
While social robots are developed to provide assistance to users through social interactions, their behaviors are dominantly pre-programmed and remote-controlled. Despite the numerous robot control architectures being developed, very few…
In this paper, we present an approach to define the semantics for object-oriented modeling languages. One important property of this semantics is to support underspecified and incomplete models. To this end, semantics is given as predicates…
Deep learning's success in perception, natural language processing, etc. inspires hopes for advancements in autonomous robotics. However, real-world robotics face challenges like variability, high-dimensional state spaces, non-linear…
This chapter discusses the current state of the art, and emerging research challenges, for metamodelling. In the state-of-the-art review on metamodelling, we review approaches, abstractions, and tools for metamodelling, evaluate them with…
Direct design of a robot's rendered dynamics, such as in impedance control, is now a well-established control mode in uncertain environments. When the physical interaction port variables are not measured directly, dynamic and kinematic…
In this paper we present a workflow to design and control robot manipulation behavior. To remain independent from particular robot hardware and an explicit area of application, an embedded domain specific language (eDSL) is used to describe…
In this paper, we present a planning system based on semantic reasoning for a general-purpose service robot, which is aimed at behaving more intelligently in domains that contain incomplete information, under-specified goals, and dynamic…
Model-based Reinforcement Learning and Control have demonstrated great potential in various sequential decision making problem domains, including in robotics settings. However, real-world robotics systems often present challenges that limit…
Real-time adaptation is imperative to the control of robots operating in complex, dynamic environments. Adaptive control laws can endow even nonlinear systems with good trajectory tracking performance, provided that any uncertain dynamics…
The advantage of modular self-reconfigurable robot systems is their flexibility, but this advantage can only be realized if appropriate configurations (shapes) and behaviors (controlling programs) can be selected for a given task. In this…