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Archivio digitale delle tesi discusse presso l’Università di Pisa

Tesi etd-05102006-114606


Tipo di tesi
Tesi di dottorato di ricerca
Autore
Ferro, Marcello
Indirizzo email
marcello.ferro@ing.unipi.it
URN
etd-05102006-114606
Titolo
High Efficiency Real-Time Sensor and Actuator Control and Data Processing
Settore scientifico disciplinare
ING-INF/06
Corso di studi
AUTOMATICA, ROBOTICA E BIOINGEGNERIA
Relatori
relatore Prof. De Rossi, Danilo
Parole chiave
  • biomimetics
  • data analysis
  • human-machine interface
  • imitation
  • learning
  • life-like artifact
  • multi-task data processing
  • neural networks
  • pattern recognition
  • real-time multi-transducer networks
  • robot-based treatment method
  • sensory fusion
  • social attention
Data inizio appello
21/04/2006
Consultabilità
Completa
Riassunto
The advances in sensor and actuator technology foster the use of large multitransducer networks in many different fields. The increasing complexity of such networks poses problems in data processing, especially when high-efficiency is required for real-time applications. In fact, multi-transducer data processing usually consists of interconnection and co-operation of several modules devoted to process different tasks. Multi-transducer network modules often include tasks such as control, data acquisition, data filtering interfaces, feature selection and pattern analysis. Heterogeneous techniques derived from chemometrics, neural networks, fuzzy-rules used to implement such tasks may introduce module interconnection and co-operation issues. To help dealing with these problems the author here presents a software library architecture for a dynamic and efficient management of multi-transducer data processing and control techniques. The framework’s base architecture and the implementation details of several extensions are described. Starting from the base models available in the framework core dedicated models for control processes and neural network tools have been derived. The Facial Automaton for Conveying Emotion (FACE) has been used as a test field for the control architecture.
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