342 research outputs found

    A Reference Software Architecture for Social Robots

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    Social Robotics poses tough challenges to software designers who are required to take care of difficult architectural drivers like acceptability, trust of robots as well as to guarantee that robots establish a personalised interaction with their users. Moreover, in this context recurrent software design issues such as ensuring interoperability, improving reusability and customizability of software components also arise. Designing and implementing social robotic software architectures is a time-intensive activity requiring multi-disciplinary expertise: this makes difficult to rapidly develop, customise, and personalise robotic solutions. These challenges may be mitigated at design time by choosing certain architectural styles, implementing specific architectural patterns and using particular technologies. Leveraging on our experience in the MARIO project, in this paper we propose a series of principles that social robots may benefit from. These principles lay also the foundations for the design of a reference software architecture for Social Robots. The ultimate goal of this work is to establish a common ground based on a reference software architecture to allow to easily reuse robotic software components in order to rapidly develop, implement, and personalise Social Robots

    Prospection in cognition: the case for joint episodic-procedural memory in cognitive robotics

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    Prospection lies at the core of cognition: it is the means by which an agent \u2013 a person or a cognitive robot \u2013 shifts its perspective from immediate sensory experience to anticipate future events, be they the actions of other agents or the outcome of its own actions. Prospection, accomplished by internal simulation, requires mechanisms for both perceptual imagery and motor imagery. While it is known that these two forms of imagery are tightly entwined in the mirror neuron system, we do not yet have an effective model of the mentalizing network which would provide a framework to integrate declarative episodic and procedural memory systems and to combine experiential knowledge with skillful know-how. Such a framework would be founded on joint perceptuo-motor representations. In this paper, we examine the case for this form of representation, contrasting sensory-motor theory with ideo-motor theory, and we discuss how such a framework could be realized by joint episodic-procedural memory. We argue that such a representation framework has several advantages for cognitive robots. Since episodic memory operates by recombining imperfectly recalled past experience, this allows it to simulate new or unexpected events. Furthermore, by virtue of its associative nature, joint episodic-procedural memory allows the internal simulation to be conditioned by current context, semantic memory, and the agent\u2019s value system. Context and semantics constrain the combinatorial explosion of potential perception-action associations and allow effective action selection in the pursuit of goals, while the value system provides the motives that underpin the agent\u2019s autonomy and cognitive development. This joint episodic-procedural memory framework is neutral regarding the final implementation of these episodic and procedural memories, which can be configured sub-symbolically as associative networks or symbolically as content-addressable image databases and databases of motor-control scripts

    Maintaining Structured Experiences for Robots via Human Demonstrations: An Architecture To Convey Long-Term Robot\u2019s Beliefs

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    This PhD thesis presents an architecture for structuring experiences, learned through demonstrations, in a robot memory. To test our architecture, we consider a specific application where a robot learns how objects are spatially arranged in a tabletop scenario. We use this application as a mean to present a few software development guidelines for building architecture for similar scenarios, where a robot is able to interact with a user through a qualitative shared knowledge stored in its memory. In particular, the thesis proposes a novel technique for deploying ontologies in a robotic architecture based on semantic interfaces. To better support those interfaces, it also presents general-purpose tools especially designed for an iterative development process, which is suitable for Human-Robot Interaction scenarios. We considered ourselves at the beginning of the first iteration of the design process, and our objective was to build a flexible architecture through which evaluate different heuristic during further development iterations. Our architecture is based on a novel algorithm performing a oneshot structured learning based on logic formalism. We used a fuzzy ontology for dealing with uncertain environments, and we integrated the algorithm in the architecture based on a specific semantic interface. The algorithm is used for building experience graphs encoded in the robot\u2019s memory that can be used for recognising and associating situations after a knowledge bootstrapping phase. During this phase, a user is supposed to teach and supervise the beliefs of the robot through multimodal, not physical, interactions. We used the algorithm to implement a cognitive like memory involving the encoding, storing, retrieving, consolidating, and forgetting behaviours, and we showed that our flexible design pattern could be used for building architectures where contextualised memories are managed with different purposes, i.e. they contains representation of the same experience encoded with different semantics. The proposed architecture has the main purposes of generating and maintaining knowledge in memory, but it can be directly interfaced with perceiving and acting components if they provide, or require, symbolical knowledge. With the purposes of showing the type of data considered as inputs and outputs in our tests, this thesis also presents components to evaluate point clouds, engage dialogues, perform late data fusion and simulate the search of a target position. Nevertheless, our design pattern is not meant to be coupled only with those components, which indeed have a large room of improvement

    The active inference approach to ecological perception: general information dynamics for natural and artificial embodied cognition

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    The emerging neurocomputational vision of humans as embodied, ecologically embedded, social agents—who shape and are shaped by their environment—offers a golden opportunity to revisit and revise ideas about the physical and information-theoretic underpinnings of life, mind, and consciousness itself. In particular, the active inference framework (AIF) makes it possible to bridge connections from computational neuroscience and robotics/AI to ecological psychology and phenomenology, revealing common underpinnings and overcoming key limitations. AIF opposes the mechanistic to the reductive, while staying fully grounded in a naturalistic and information-theoretic foundation, using the principle of free energy minimization. The latter provides a theoretical basis for a unified treatment of particles, organisms, and interactive machines, spanning from the inorganic to organic, non-life to life, and natural to artificial agents. We provide a brief introduction to AIF, then explore its implications for evolutionary theory, ecological psychology, embodied phenomenology, and robotics/AI research. We conclude the paper by considering implications for machine consciousness

    Interactive Sound in Performance Ecologies: Studying Connections among Actors and Artifacts

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    This thesis’s primary goal is to investigate performance ecologies, that is the compound of humans, artifacts and environmental elements that contribute to the result of a per- formance. In particular, this thesis focuses on designing new interactive technologies for sound and music. The goal of this thesis leads to the following Research Questions (RQs): • RQ1 How can the design of interactive sonic artifacts support a joint expression across different actors (composers, choreographers, and performers, musicians, and dancers) in a given performance ecology? • RQ2 How does each different actor influence the design of different artifacts, and what impact does this have on the overall artwork? • RQ3 How do the different actors in the same ecology interact, and appropriate an interactive artifact? To reply to these questions, a new framework named ARCAA has been created. In this framework, all the Actors of a given ecology are connected to all the Artifacts throughout three layers: Role, Context and Activity. This framework is then applied to one systematic literature review, two case studies on music performance and one case study in dance performance. The studies help to better understand the shaded roles of composers, per- formers, instrumentalists, dancers, and choreographers, which is relevant to better design interactive technologies for performances. Finally, this thesis proposes a new reflection on the blurred distinction between composing and designing a new instrument in a context that involves a multitude of actors. Overall, this work introduces the following contributions to the field of interaction design applied to music technology: 1) ARCAA, a framework to analyse the set of inter- connected relationship in interactive (music) performances, validated through 2 music studies, 1 dance study and 1 systematic literature analysis; 2) Recommendations for de- signing music interactive system for performance (music or dance), accounting for the needs of the various actors and for the overlapping on music composition and design of in- teractive technology; 3) A taxonomy of how scores have shaped performance ecologies in NIME, based on a systematic analysis of the literature on score in the NIME proceedings; 4) Proposal of a methodological approach combining autobiographical and idiographical design approaches in interactive performances.O objetivo principal desta tese é investigar as ecologias performativas, conjunto formado pelos participantes humanos, artefatos e elementos ambientais que contribuem para o resultado de uma performance. Em particular, esta tese foca-se na conceção de novas tecnologias interativas para som e música. O objetivo desta tese originou as seguintes questões de investigação (Research Questions RQs): • RQ1 Como o design de artefatos sonoros interativos pode apoiar a expressão con- junta entre diferentes atores (compositores, coreógrafos e performers, músicos e dançarinos) numa determinada ecologia performativa? • RQ2 Como cada ator influencia o design de diferentes artefatos e que impacto isso tem no trabalho artístico global? • RQ3 Como os diferentes atores de uma mesma ecologia interagem e se apropriam de um artefato interativo? Para responder a essas perguntas, foi criado uma nova framework chamada ARCAA. Nesta framework, todos os atores (Actores) de uma dada ecologia estão conectados a todos os artefatos (Artefacts) através de três camadas: Role, Context e Activity. Esta framework foi então aplicada a uma revisão sistemática da literatura, a dois estudos de caso sobre performance musical e a um estudo de caso em performance de dança. Estes estudos aju- daram a comprender melhor os papéis desempenhados pelos compositores, intérpretes, instrumentistas, dançarinos e coreógrafos, o que é relevante para melhor projetar as tec- nologias interativas para performances. Por fim, esta tese propõe uma nova reflexão sobre a distinção entre compor e projetar um novo instrumento num contexto que envolve uma multiplicidade de atores. Este trabalho apresenta as seguintes contribuições principais para o campo do design de interação aplicado à tecnologia musical: 1) ARCAA, uma framework para analisar o conjunto de relações interconectadas em performances interativas, validado através de dois estudos de caso relacionados com a música, um estudo de caso relacionado com a dança e uma análise sistemática da literatura; 2) Recomendações para o design de sistemas interativos musicais para performance (música ou dança), tendo em conta as necessidades dos vários atores e a sobreposição entre a composição musical e o design de tecnologia interactiva; 3) Uma taxonomia sobre como as partituras musicais moldaram as ecologias performativas no NIME, com base numa análise sistemática da literatura dos artigos apresentados e publicados nestas conferência; 4) Proposta de uma aborda- gem metodológica combinando abordagens de design autobiográfico e idiográfico em performances interativas

    Prospection in cognition : The case for joint episodic-procedural memory in cognitive robotics

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    Prospection lies at the core of cognition: it is the means by which an agent — a person or a cognitive robot — shifts its perspective from immediate sensory experience to anticipate future events, be they the actions of other agents or the outcome of its own actions. Prospection, accomplished by internal simulation, requires mechanisms for both perceptual imagery and motor imagery. While it is known that these two forms of imagery are tightly entwined in the mirror neuron system, we do not yet have an effective model of the mentalizing network which would provide a framework to integrate declarative episodic and procedural memory systems and to combine experiential knowledge with skillful know-how. Such a framework would be founded on joint perceptuo-motor representations. In this paper we examine the case for this form of representation, contrasting sensory-motor theory with ideo-motor theory, and we discuss how such a framework could be realized by joint episodic-procedural memory. We argue that such a representation framework has several advantages for cognitive robotics. Since episodic memory operates by recombining imperfectly recalled past experience, this allows it to simulate new or unexpected events. Furthermore, by virtue of its associative nature, joint episodic-procedural memory allows the internal simulation to be conditioned by current context, semantic memory, and the agent's value system. Context and semantics constrain the combinatorial explosion of potential perception-action associations and allow effective action selection in the pursuit of goals, while the value system provides the motives that underpin the agent's autonomy and cognitive development. This joint episodic-procedural memory framework is neutral regarding the final implementation of these episodic and procedural memories, which can be configured sub-symbolically as associative networks or symbolically as content-addressable image databases and databases of motor-control scripts
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