Self-adaptation can be used in robotics to increase system robust- ness and reliability. This work describes the Metacontrol method for self-adaptation in robotics. Particularly, it details how the MROS (Metacontrol for ROS Systems) framework implements and pack- ages Metacontrol, and it demonstrate how MROS can be applied in a navigation scenario where a mobile robot navigates in a factory floor. Video: https://www.youtube.com/watchvISe9aMskJuE

Once deployed in the real world, autonomous underwater vehicles (AUVs) are out of reach for human supervision yet need to take decisions to adapt to unstable and unpredictable environments. To facilitate research on self-adaptive AUVs, this paper presents SUAVE, an exemplar for two-layered system-level adaptation of AUVs, which clearly separates the application and self-adaptation concerns. The exemplar focuses on a mission for underwater pipeline inspection by a single AUV, implemented as a ROS 2-based system. This mission must be completed while simultaneously accounting for uncertainties such as thruster failures and unfavorable environmental conditions. The paper discusses how SUAVE can be used with different self-adaptation frameworks, illustrated by an experiment using the Metacontrol framework to compare AUV behavior with and without self-adaptation. The experiment shows that the use of Metacontrol to adapt the AUV during its mission improves its performance when measured by the overall time taken to complete the mission or the length of the inspected pipeline.

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.

The functional capabilities that consciousness seems to provide to biological systems can supply valuable principles in the design of more autonomous and robust technical systems. These functional concepts keep a notable similarity to those underlying the notion of operating system in software engineering, which allows us to specialize the computer metaphor for the mind into that of the operating system metaphor for consciousness. In this article, departing from these ideas and a model-based theoretical framework for cognition, we present an architectural proposal for machine consciousness, called the Operative Mind. According to it, machine consciousness could be implemented as a set of services, in an operative system fashion, based on modeling of the own control architecture, that supervise the adequacy of the system architectural structure to the current objectives, triggering and managing adaptativity mechanisms.

The reflection on the nature of mind has a long history. In western tradition, this reflection has mostly taken place along the so-called dualist approach, where mind and body completely have different characteristics and even natures. In this dualistic context for understanding thought (and life!), the biggest problem has always been how these two realms-the physical and the mental-could possibly interact: the mind-body problem is the unavoidable sequel to this dualist standpoint. The embodied cognition movement tries to reconcile this apparently multiple qualities (. duality and unity) of human experience by means of analyzing the ways in which the body may affect cognition: supporting, sustaining, shaping, etc. Mind and body cannot be separated because cognitive agents think with the body. Mind, as a separate entity, is in the eye of the beholder. This chapter contends that the mind-body problem is not a problem of minds and bodies in the world-that is, a physical problem of interaction-but simply an artificial, conceptual problem for philosophers/scientists. The way to come out of the problem is to realize that minds and bodies are not separate entities, but what are separate are the mental concepts used in thinking about them; that is, what most thinkers use to think about minds and bodies as ontologically fully separate entities. However this way of thinking is misleading. Minds can be reduced to bodies because they are simply processes that run on them.