The lack of a well established theory of consciousness is a major difficulty in the construction of machines that express some of the functionalities associated to them. The ASys long term project intends the construction of assets for engineering any-scale, self-aware autonomous systems. A core element in this effort is the proposal of an architecture for consciousness of general applicability. In this article we analyze some of the current problems present in the construction of machines based on cognitive models and propose a model-based strategy to enhance the rigor of the theorization on consciousness and its mapping into realizations in technical systems.@en

Ontologies provide a common conceptualisation that can be shared by all stakeholders involved in an engineering development process. They provide a good means to analyse the knowledge domain, allowing to separate the descriptive and the problem-solving knowledge. They can also be as generic as needed allowing its reuse and easy extension. These features made ontologies useful for representing the knowledge of software engineering techniques applied to autonomous systems. This work describes an ontology-based framework consisting of two intertwined elements: a domain ontology for autonomous systems (OASys) to capture any autonomous system's structure, function, and behaviour; and an ontology-based engineering methodology that generates models for autonomous systems, based on the knowledge contained in OASys and other domain ontologies. Both elements have been used in a case study to assess the suitability of the developed framework.@en

This paper describes the development of an ontology for autonomous systems, as the initial stage of a research programme on autonomous systems' engineering within a model-based control approach. The ontology aims at providing a unified conceptual framework for the autonomous systems' stakeholders, from developers to software engineers. The modular ontology contains both generic and domain-specific concepts for autonomous systems description and engineering. The ontology serves as the basis in a methodology to obtain the autonomous system's conceptual models. The objective is to obtain and to use these models as main input for the autonomous system's model-based control system.@en

Autonomous systems refer to systems capable of operating in a real world environment without any form of external control for extended periods of time. Autonomy is a desired goal for every system as it improves its performance, safety and profit. Ontologies are a way to conceptualize the knowledge of a specific domain. In this paper an ontology for the description of autonomous systems as well as for its development (engineering) is presented and applied to a process. This ontology is intended to be applied and used to generate final applications following a model driven methodology.@en

Robot control software endows robots with advanced capabilities for autonomous operation, such as navigation, object recognition or manipulation, in unstructured and dynamic environments. However, there is a steady need for more robust operation, where robots should perform complex tasks by reliably exploiting these novel capabilities. Mission-level resilience is required in the presence of component faults through failure recovery.To address this challenge, a novel self-adaptation framework based on functional knowledge for augmented autonomy is presented. A metacontroller is integrated on top of the robot control system,and it uses an explicit run-time model of the robot’s controller and its mission to adapt to operational changes. The model is grounded on a functional ontology that relates the robot’s mission with the robot’s architecture, and it is generated during the robot’s development from its engineering models. Advantages are discussed from both theoretical and practical viewpoints. An application example in a real autonomous mobile robot is provided. In this example, the generic metacontroller uses the robot’s functional model to adapt the control architecture to recover from a sensor failure.@en

Ontologies provide a common conceptualisation that can be shared by all stakeholders in an engineering development process. They provide a good means to analyse the domain, allowing to separate descriptive from problem-solving knowledge. Our research programme on autonomous systems considered an ontology as the adequate mechanism to conceptualise the autonomous systems domain, and the software engineering techniques applied to such systems. This paper describes the ontological engineering process of such an ontology: OASys (Ontology for Autonomous Systems). Its development considered different stages: the specification of the requirements to be fulfilled by the ontology; the extraction of the actual features needed to implement the desired requirements; the conceptualisation phase with the design decisions to integrate the different domains, theories and techniques addressed by the ontological elements; and finally, the implementation of the ontology, which integrates both ontology engineering and software engineering approaches by using UML as the implementation language.@en

Construction of robotic controllers has been usually done by the instantiation of specific architectural designs. The ASys design strategy described in this work addresses the synthesis of custom robot architectures by means of a requirements-driven application of universal design patterns. In this paper we present three of these patterns -the Epistemic Control Loop, the MetaControl and the Deep Model Reflection patterns- that constitute the core of a pattern language for a new class of adaptive and robust control architectures for autonomous robots. A reference architecture for self-aware autonomous systems is synthesised from these patterns and demonstrated in the control of an autonomous mobile robot. The term "autonomous" gains a deeper significance in this context of reflective, pattern based controllers.@en

This paper describes a work in progress on an ontology-based approach for autonomous system engineering. This is part of the ASys research programme which focuses on the development of a technology for autonomous systems product-line engineering. Such technology will comprehend from platform technology to designs of intelligent autonomous systems and support methodologies. Within this programme, a domain-ontology for autonomous systems (OASys) has been developed to describe the autonomous system's domain. OASys will be used as core software asset for the analysis, design, implementation, and run-time operation of any autonomous system. Two testbeds are being developed to test OASys's applicability: a mobile robot-based application, and the control system of a chemical reactor.@en

There is an increasing demand for more autonomous systems. Enhancing systems with self-aware and self- adaptation capabilities can provide a solution to meet resilience needs. This article proposes a general design solution to build autonomous systems capable of run-time reconfiguration. The solution leverages Model-Driven Engineering with Model-Based Cognitive Control. The key idea is the integration of a metacontroller in the control architecture of the autonomous system, capable of perceiving the dysfunctional components of the control system and reconfiguring it, if necessary, at runtime. At the core of the metacontroller's operation lies a model of the system's functional architecture, which can be generated from the engineering modeling of the system.@en

Our research focuses on engineering processes for autonomous intelligent systems construction with a life-cycle holistic view, by means of a model-based framework. The conceptual core of the framework is ontologically-driven. Our ontological approach consists of two elements. The first one is a domain Ontology for Autonomous Systems (OASys) to capture the autonomous system structure, function and behaviour. The second element is an Ontology-driven Engineering Methodology (ODEM) to develop the target autonomous system. This methodology is based on Model-based Systems Engineering and produces models of the system as core assets. These models are used through the whole system life-cycle, from implementation or validation to operation and maintenance. On the application side, the ontological framework has been used to develop a metacontrol engineering technology for autonomous systems, the OM Engineering Process (OMEP), to improve their runtime adaptivity and resilience. OMEP has been applied to a mobile robot in the form of a metacontroller built on top of the robot's control architecture. It exploits a functional model of the robot (TOMASys Model) to reconfigure its control if required by the situation at runtime. The functional model is based on a metamodel about controller function and structure using concepts form the ontology. The metacontroller was developed using the ontology-driven methodology and a robot control reference architecture.@en

Conceptual modelling aims at identifying, and characterising the entities and the relationships of a selected phenomenon in some domain. The obtained conceptual models express the meaning of the concepts used by domain experts, and the relationships between them. An ontology is a for- mal specification of a common conceptualisation shared by stakeholders and experts in a domain. Ontologies can serve as the semantic support for conceptual modelling, guiding and constraining the intended meaning of the conceptual models. We have followed this approach in our model-based control systems, by developing a domain ontology and an ontology- based methodology to support the conceptual modelling of autonomous systems. The ontology for autonomous systems captures the ontological elements to describe an autonomous system's structure, function, and behaviour. The methodology exploits the ontology to generate the conceptual models for a generic engineering process. Both elements have been used in case studies to obtain conclusions on the suitability of the developed ontology and its application in the model-based engineering of autonomous systems.@en

Much is being done in an attempt to transfer emotional mechanisms from reverse-engineered biology into social robots. There are two basic approaches: the imitative display of emotion -e.g. to intend more human-like robots- and the provision of architectures with intrinsic emotion -in the hope of enhancing behavioral aspects. This paper focuses on the second approach, describing a core vision regarding the integration of cognitive, emotional and autonomic aspects in social robot systems. This vision has evolved as a result of the efforts in consolidating the models extracted from rat emotion research and their implementation in technical use cases based on a general systemic analysis in the framework of the ICEA and C3 projects. The desire for generality of the approach intends obtaining universal theories of integrated -autonomic, emotional, cognitive- behavior. The proposed conceptualizations and architectural principles are then captured in a theoretical framework: ASys - The Autonomous Systems Framework.@en