Scheda programma d'esame
SOCIAL ROBOTICS AND AFFECTIVE COMPUTING
ENZO PASQUALE SCILINGO
Academic year2018/19
CourseBIONICS ENGINEERING
Code702II
Credits12
PeriodSemester 1 & 2
LanguageEnglish

ModulesAreaTypeHoursTeacher(s)
AFFECTIVE COMPUTINGING-INF/06LEZIONI60
ENZO PASQUALE SCILINGO unimap
SOCIAL ROBOTICSINF/01LEZIONI60
LORENZO COMINELLI unimap
DANIELE MAZZEI unimap
Obiettivi di apprendimento
Learning outcomes
Conoscenze

Modulo di Affective Computing: Lo studente acquisirà conoscenze relative alle emozioni e alle sue correlazioni con i segnali fisiologici. Oltre alle emozioni verranno studiati anche i correlati fisiologici con i disordini mentali 

modulo di social robotics: lo studente acquisirà conoscenze relative al mondo dei robot atti all'interazione sociale, degli strumenti di programmazione di quest'utlimi e dei paradigmi di progettazione e test di questi apparati

Knowledge

Affective Computing: Students will gain knowledge about theories of emotion and mood disorders. Specifically they will learn how to model emotions and how to correlate them to the patterns of physiological signals. 

 

Social Robitcs: students will acquire knowledge related to the world of robots suitable for social interaction, the programming tools, the design, the prototyping and the testing of paradigms of these machines

Modalità di verifica delle conoscenze

Modulo di Affective Computing: Le conoscenze acquisite verranno verificate attraverso test in itinere e finale

 

Modulo di Social Robotics: Le conoscenze acquisite verranno verificate attraverso test in itinere e finale

Assessment criteria of knowledge

both modules: The gained knowledge will be assessed through ongoing tests.

Capacità

Modulo di Affective Computing: Lo studente sarà in grado di capire le relazioni tra pattern di segnali fisioligici e emozioni, quindi sarà in grado di identificare e caratterizzare le emozioni oltre che capire la neurofisiologia dei disordini mentali. 

 

Modulo di Social Robotics: Lo studente sarà in grado di progettare in termini funzionali e di definire uno schema di comportamento e relazione uomo-macchina per un robot sociale ma anche per un oggetto "smart" e/o un'applicazione mobile. 

Skills

Affective computing: Students will be able to process physiological data applying advanced linear and nonlinear methods trying to correlate that to the emotional experiences.  

 

Social Robotics: students will be able to design and define (in functional terms)a human-machine behavior and relationship scheme for a social robot but also for a "smart" object and/or a mobile application.

Modalità di verifica delle capacità

Modulo di Affective Computing: Progetto sperimentale finale e prova orale

Modulo di Social Robotics: Progetto sperimentale finale e prova orale

Assessment criteria of skills

both modules: It is planned a final project with an experimental paradigm. 

Comportamenti

Modulo di Affective Computing: Capacità di progettare un protocollo sperimentale e definire un paradigma dettagliato

 

Modulo di Social Robotics: Lo studente potrà acquisire e/o sviluppare sensibilità alle problematiche di interazione sociale ed emaptica fra uomo e robot e fra uomo e macchina. Lo studente potrà inoltre saper gestire responsabilità di esecuzione e formalizzazione di un progetto di design di prodotto 

Behaviors

Affective computing: Real experimental data will be collected with a suitable protocol 

 

Social Robotics: student will be able to acquire and/or develop sensitivity to the problems of social and hemapic interaction between humans and robots and between humans and machines. The students will also be able to manage responsibility for the execution and formalization of a product design project

 

Modalità di verifica dei comportamenti

Modulo di Affective Computing: Progetto sperimentale finale

Modulo di Social Robotics: Progetto sperimentale finale

Assessment criteria of behaviors

both modeuls: Assessment will be done through the design a final experimental protocol

Prerequisiti (conoscenze iniziali)

N/A

Prerequisites

N/A

Indicazioni metodologiche

Modulo di Affective Computing: Lezioni frontali e esercitazioni di laboratorio

Modulo di Social Robotics: Lezioni frontali e esercitazioni di laboratorio

Teaching methods

both modules: Frontal lesson and laboratory practice

Programma (contenuti dell'insegnamento)

Modulo di Affective Computing: 

Limbic system and hemisphere pre-cortex

Autonomic nervous system: fight or flight and rest and disgest theories

Theories of emotion: how emotions arise

Heart rate variability: methods of analysis and feature extraction

Respiration activity: methods of analysis and feature extraction

Complexity and chaos theory

A special focus on DFA and Entropy

Non-linear methods for feature extraction from physiological signals

Examples of practical applications on non-linear methods in the emotional domain 

Time-varying Nonlinear Models of Human Heartbeat Dynamics 

Examples of practical applications on point process in the filed of affective computing 

Electrodermal activity: models, methods of analysis and feature extraction 

Examples of practical applications electrodermal activity and emotions

EEG: methods of analysis and feature extraction

Examples of practical applications on EEG , BCI and emotions 

Speech voice processing: models, methods of analysis and feature extraction

Examples of practical applications on emotional speech analysis

Neuroimaging in psychatry

Sleep and dream analysis

Planning and timeline of the assigned projects

 

Modulo di Socila Robotics:

  • Introduction: Definition of robot and social robot, Examples of animal pet like social robots, Example of human like social robots, Definition and basics of The internet of Things 
  • Intelligent Agents 
  • Expert Systems
  • AI for robots: The Embodied Mind 
  • Robotic Perception: sensors, actuators, acquisition devices a 
  • Hands-On Clips expert system
  • Robot Control hardware and high level software 
  • YARP hands-on (3h)
  • Robot low-level control software and IOT dev tool 
  • clouds for Robot and IOT 
  • Chatbot in the social robot and IOT era
Syllabus

Limbic system and hemisphere pre-cortex

Autonomic nervous system: fight or flight and rest and disgest theories

Theories of emotion: how emotions arise

Heart rate variability: methods of analysis and feature extraction

Respiration activity: methods of analysis and feature extraction

Complexity and chaos theory

A special focus on DFA and Entropy

Non-linear methods for feature extraction from physiological signals

Examples of practical applications on non-linear methods in the emotional domain 

Time-varying Nonlinear Models of Human Heartbeat Dynamics 

Examples of practical applications on point process in the filed of affective computing 

Electrodermal activity: models, methods of analysis and feature extraction 

Examples of practical applications electrodermal activity and emotions

EEG: methods of analysis and feature extraction

Examples of practical applications on EEG , BCI and emotions 

Speech voice processing: models, methods of analysis and feature extraction

Examples of practical applications on emotional speech analysis

Neuroimaging in psychatry

Sleep and dream analysis

Planning and timeline of the assigned projects

 

Social Robotics module:

  • Introduction: Definition of robot and social robot, Examples of animal pet like social robots, Example of human like social robots, Definition and basics of The internet of Things 
  • Intelligent Agents 
  • Expert Systems
  • AI for robots: The Embodied Mind 
  • Robotic Perception: sensors, actuators, acquisition devices a 
  • Hands-On Clips expert system
  • Robot Control hardware and high level software 
  • YARP hands-on (3h)
  • Robot low-level control software and IOT dev tool 
  • clouds for Robot and IOT 
  • Chatbot in the social robot and IOT era
Bibliografia e materiale didattico

Modulo di Affective Computing: Appunti e dispense forniti dal docente

Modulo di Social Robotics: Appunti e dispense forniti dal docente

Bibliography

both modules: Notes provided by the teacher

Indicazioni per non frequentanti

N/A

Non-attending students info

N/A

Modalità d'esame

Modulo di Affective Computing: Progetto finale più prova pratica

Modulo di Social Robotics: Progetto finale più prova orale

Assessment methods

both modules: Practical and oral test

Altri riferimenti web

N/A

Additional web pages

N/A

Note

N/A

Notes

N/A

Updated: 03/10/2018 16:14