Abel: Integrating Humanoid Body, Emotions, and Time Perception to Investigate Social Interaction and Human Cognition

Humanoids have been created for assisting or replacing humans in many applications, providing encouraging results in contexts where social and emotional interaction is required, such as healthcare, education, and therapy. Bioinspiration, that has often guided the design of their bodies and minds, made them also become excellent research tools, probably the best platform by which we can model, test, and understand the human mind and behavior. Driven by the aim of creating a believable robot for interactive applications, as well as a research platform for investigating human cognition and emotion, we are constructing a new humanoid social robot: Abel. In this paper, we discussed three of the fundamental principles that motivated the design of Abel and its cognitive and emotional system: hyper-realistic humanoid aesthetics, human-inspired emotion processing, and human-like perception of time. After reporting a brief state-of-the-art on the related topics, we present the robot at its stage of development, what are the perspectives for its application, and how it could satisfy the expectations as a tool to investigate the human mind, behavior, and consciousness

SEAI: Social Emotional Artificial Intelligence Based on Damasio's Theory of Mind

A socially intelligent robot must be capable to extract meaningful information in real-time from the social environment and react accordingly with coherent human-like behaviour. Moreover, it should be able to internalise this information, to reason on it at a higher abstract level, build its own opinions independently and then automatically bias the decision-making according to its unique experience. In the last decades, neuroscience research highlighted the link between the evolution of such complex behaviour and the evolution of a certain level of consciousness, which cannot leave out of a body that feels emotions as discriminants and prompters. In order to develop cognitive systems for social robotics with greater human-likeliness, we used an "understanding by building" approach to model and implement a well-known theory of mind in the form of an artificial intelligence, and we tested it on a sophisticated robotic platform. The name of the presented system is SEAI (Social Emotional Artificial Intelligence), a cognitive system specifically conceived for social and emotional robots. It is designed as a bio-inspired, highly modular, hybrid system with emotion modelling and high-level reasoning capabilities. It follows the deliberative/reactive paradigm where a knowledge-based expert system is aimed at dealing with the high-level symbolic reasoning, while a more conventional reactive paradigm is deputed to the low-level processing and control. The SEAI system is also enriched by a model which simulate the Damasio's theory of consciousness and the theory of Somatic Markers. After a review of similar bio-inspired cognitive systems, we present the scientific foundations and their computational formalisation at the basis of the SEAI framework. Then, a deeper technical description of the architecture is disclosed underlining the numerous parallelisms with the human cognitive system. Finally, the influence of artificial emotions and feelings, and their link with the robot's beliefs and decisions have been tested in a physical humanoid involved in Human-Robot Interaction (HRI)

Fashion communication research: A way ahead

This document, designed and written during the conference FACTUM19, has two main goals: to help consolidate Fashion Communication as an academic field, and to support an international and interdisciplinary network of scholars in the area, whose collaboration may lead to a larger body of research and, in turn, to further academic recognition. To do so, it outlines main research topics, approaches and challenges, as well as related industry issues and learning dimensions

A Multimodal Perception Framework for Users Emotional State Assessment in Social Robotics

In this work, we present an unobtrusive and non-invasive perception framework based on the synergy between two main acquisition systems: the Touch-Me Pad, consisting of two electronic patches for physiological signal extraction and processing; and the Scene Analyzer, a visual-auditory perception system specifically designed for the detection of social and emotional cues. It will be explained how the information extracted by this specific kind of framework is particularly suitable for social robotics applications and how the system has been conceived in order to be used in human-robot interaction scenarios

The EASEL project: Towards educational human-robot symbiotic interaction

This paper presents the EU EASEL project, which explores the potential impact and relevance of a robot in educational settings. We present the project objectives and the theorectical background on which the project builds, briefly introduce the EASEL technological developments, and end with a summary of what we have learned from the evaluation studies carried out in the project so far

DESIGN AND IMPLEMENTATION OF A BIO-INSPIRED COGNITIVE SYSTEM FOR SOCIAL ROBOTICS: FROM EMOTION TO CONSCIOUSNESS.

In quanto esseri umani, siamo sempre stati affascinati dalla possibilità di creare macchine che non abbiano solo sembianze umane, ma siano anche emotive, sensibili e con capacità comunicative simili a quelle della nostra specie. Questa spinta, questo interesse, combinati con gli enormi progressi avvenuti nell'ambito dei sistemi hardware, della robotica e dell'intelligenza artificiale, hanno portato alla creazione della robotica sociale. Ad oggi, la Social Robotics è sicuramente una delle branche più innovative e attraenti della robotica, nonchè una realtà scientifica eterogenea contaminata da discipline quali le neuroscienze e la psicologia, ma anche dalla filosofia della mente e dallo studio della comunicazione e del linguaggio. Questa tesi di dottorato presenta la progettazione e lo sviluppo di un sitema cognitivo artificale, bio-ispirato, specificatamente concepito per robot sociali. I requisiti fondamentali per la progettazione di una mente di robot sociale sono stati ricavati da un approfondito studio dello stato dell'arte di sistemi di controllo esistenti e applicati, o sperimentati, da altri istituti di ricerca. Queste nozioni principali sono state incrociate con altre, derivanti dallo studio di teorie neuroscientifiche. Sono stati studiati con particolare interesse quei meccanismi umani che sottostanno alla creazione delle emozioni e fanno sì che queste ultime siano una componente fondamentale per la formazione delle nostre decisioni, i nostri comportamenti e per la creazione di quello che definiamo la nostra coscienza. Il sistema cognitivo che è stato sviluppato sulla base di questi studi è un'architettura di controllo ibrida reattiva/deliberativa dove vengono utilizzati due differenti approcci di programmazione. Un'architettura modulare per controllare umanoidi, robot altamente espressivi e realistici, che grazie a questo sistema acquisiscono la capacità di comprendere, elaborare ed esprimere emozioni, interagendo con interlocutori umani in modo naturale. In particolare, il sistema cognitivo presentato è ispirato alla teoria della mente di Antonio Damasio e al meccanismo dei marcatori somatici da lui descritto. Implementato come sistema esperto basato su motore di regole, il sistema di intelligenza artificiale è capace di creare catene di ragionamento, riprodurre emozioni artificiali e modulare il comportamento del robot, in accordo con l'ambiente sociale in cui si trova immerso. All'interno di questo elaborato, verrà inoltre descritta dettagliatamente l'integrazione del sistema cognitivo in un robot sociale chiamato F.A.C.E. (Facial Automaton for Conveying Emotions), un umanoide altamente realistico dotato di una maschera facciale in materiale bio-ispirato che viene attuata al fine di rappresentare, e trasmettere, emozioni umane. Il robot FACE è stata la piattaforma robotica principale sulla quale sono stati testati i moduli software che compongono il sistema cognitivo. Veranno quindi presentati i risultati di questi esperimenti, la cui maggior parte prevedono delle interazioni reali tra soggetti umani e il robot. Uno speciale rilievo verrà dato all'influenza che hanno le emozioni artificiali sul comportamento del robot, le decisioni che prende, e le opinioni che si generano automaticamente nella sua 'mente'

I-CLIPS Brain: Studio e Implementazione di un Sistema Cognitivo per Robot Sociali

Percepire e interpretare i comportamenti sociali dell’interlocutore è una sfida fondamentale per lo sviluppo di Robot Sociali. Questa nuova generazione di automi richiede un apparato sensoriale innovativo in grado di percepire il “mondo sociale ed emotivo” in cui il robot è immerso e un sistema cognitivo in grado di gestire in modo appropriato il flusso di informazioni in entrata dai sensori. E’ necessario quindi un ’cervello’ programmato allo scopo di pianificare una risposta organizzata e ponderata, dipendente dal contesto sociale, e in grado di sfruttare al massimo la capacità espressiva del sistema di attuazione. Per consentire agli scienziati di progettare modelli comportamentali per automi sociali è fondamentale sviluppare architetture di controllo facilmente utilizzabili, anche da ricercatori senza competenze tecniche di programmazione come psicologi e neuroscienziati. In questo lavoro un’architettura ibrida deliberativa/reattiva per controllare un robot umanoide sociale è stata integrata con un sistema cognitivo basato su un motore di regole. Progettazione e realizzazione del sistema complessivo prendono ispirazione dal sistema nervoso umano. In particolare, il sistema cognitivo si basa sulla teoria di Damasio. L’architettura è stata testata con il robot FACE (Facial Automaton for Conveying Emotions), sviluppato al Centro Piaggio, presso l’Università di Pisa. E’ stato modellato un comportamento sociale per rendere FACE in grado di seguire correttamente un soggetto umano durante un compito fondamentale di interazione sociale e di eseguire le espressioni facciali più appropriate in relazione al contesto sociale

Abel: Integrating Humanoid Body, Emotions, and Time Perception to Investigate Social Interaction and Human Cognition

Humanoids have been created for assisting or replacing humans in many applications, providing encouraging results in contexts where social and emotional interaction is required, such as healthcare, education, and therapy. Bioinspiration, that has often guided the design of their bodies and minds, made them also become excellent research tools, probably the best platform by which we can model, test, and understand the human mind and behavior. Driven by the aim of creating a believable robot for interactive applications, as well as a research platform for investigating human cognition and emotion, we are constructing a new humanoid social robot: Abel. In this paper, we discussed three of the fundamental principles that motivated the design of Abel and its cognitive and emotional system: hyper-realistic humanoid aesthetics, human-inspired emotion processing, and human-like perception of time. After reporting a brief state-of-the-art on the related topics, we present the robot at its stage of development, what are the perspectives for its application, and how it could satisfy the expectations as a tool to investigate the human mind, behavior, and consciousness

Fashion Communication. Cham: Springer

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Integrating CSI Sensing in Wireless Networks: Challenges to Privacy and Countermeasures

The path toward 6G is still long and blurred, but a few key points seem to be already decided: integration of many different access networks; adoption of massive MIMO technologies; use of frequencies above current radio spectrum up to THz and beyond; and inclusion of artificial intelligence and machine learning in standard management and operations. One additional point that is less discussed, but seems key for success, is the advanced use of channel state information (CSI) for both equalization and decoding purposes as well as for sensing ones. CSI-based sensing promises a plethora of new applications and a quantum leap in service personalization and customer-centric network management. At the same time, CSI analysis, being based on the physical characteristics of the propagated signal, poses novel threats to people's privacy and security: No software-based solution or cryptographic method above the physical layer can prevent the analysis of CSI. CSI analysis can reveal people's position or activity, allow tracking them, and discover details on the environment that today can be seen only with cameras or radars. In this article, we discuss the current status of CSI-based sensing and present some technologies that can protect people's privacy and at the same time allow legitimate use of the information carried by the CSI to offer better services