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

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.

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In this paper we will argue that given certain conditions for the evolution of biological controllers, they will necessarily evolve in the direction of incorporating consciousness capabilities. We will also see what are the necessary mechanics for the provision of these capabilities and extrapolate this vision to the world of artificial systems.

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The question of measuring intelligence in artifacts and, in particular, evaluating architectures for it, requires not just an understanding of the very nature of intelligence -quite elusive objective, indeed- but an appropriate stance for evaluation. In this paper we argue that it is not just the case that architectures provide intelligence, but that they really provide a substrate for intelligent behavior in the execution of a particular task. The measuring-intelligence-for-autonomy position becomes maximally relevant in the context of the increased uncertainty levels that the upcoming challenging applications are posing to cognitive architectures. This fits our understanding of intelligence as the capability of maximizing information utility.@en

In this paper we describe the approach taken in the UPM Autonomous Systems Laboratory for the development of technology of full, bounded autonomy. This effort is taking us into the study of the phenomenology of consciousness especially in relation with the construction of mechanisms for system self-awareness. The progress of this work can be tracked in our ASys and SOUL projects webpages. The ASys Project is a long-term project that deals with the development of an engineering process and a collection of assets for the implementation of autonomous systems.. The SOUL Project develops a generic architecture for self-aware autonomous systems.@en