Human-Robot Interaction Based on Introspective Capability

The paper describes a mechanism of introspection of a humanoid robot based on self observation of its running processes and sensory data. The robot builds is internal state representation by a suitable ontology: a working knowledge of its physical structure and functionalities, that it can exploit to interact with humans in order to describe, in natural language, his state and the manner in which it perceives. We report experiments performed on a humanoid robot, describing all the components necessary to implement the proposed architecture of introspection.

[1]  M. F. Porter,et al.  An algorithm for suffix stripping , 1997 .

[2]  Samuel Kaski,et al.  Mining massive document collections by the WEBSOM method , 2004, Inf. Sci..

[3]  Timo Honkela,et al.  WEBSOM - Self-organizing maps of document collections , 1998, Neurocomputing.

[4]  Robert M. Gray,et al.  An Algorithm for Vector Quantizer Design , 1980, IEEE Trans. Commun..

[5]  Robert C. Bolles,et al.  Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography , 1981, CACM.

[6]  Patrick F. Reidy.  An Introduction to Latent Semantic Analysis , 2009 .

[7]  David A. Forsyth,et al.  Object Recognition as Machine Translation: Learning a Lexicon for a Fixed Image Vocabulary , 2002, ECCV.

[8]  Alex Pentland,et al.  Human computing and machine understanding of human behavior: a survey , 2006, ICMI '06.

[9]  Salvatore Gaglio,et al.  A Framework for Sign Language Sentence Recognition by Commonsense Context , 2007, IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews).

[10]  David A. Forsyth,et al.  Matching Words and Pictures , 2003, J. Mach. Learn. Res..

[11]  Francisco J. Serón,et al.  Affective Embodied Conversational Agents for Natural Interaction , 2008 .

[12]  M. V. Velzen,et al.  Self-organizing maps , 2007 .

[13]  Samuel Kaski,et al.  Self organization of a massive document collection , 2000, IEEE Trans. Neural Networks Learn. Syst..

[14]  Chin-Hui Lee,et al.  Information fusion techniques for automatic image annotation , 2007, VISAPP.

[15]  Ignazio Infantino,et al.  Affective Human-Humanoid Interaction Through Cognitive Architecture , 2012 .

[16]  Mauro Migliardi,et al.  Enhancing Personal Efficiency with Pervasive Services and Wearable Devices , 2011, 2011 International Conference on Broadband and Wireless Computing, Communication and Applications.

[17]  Giovanni Pilato,et al.  Sub-Symbolic Semantic Layer in Cyc for Intuitive Chat-Bots , 2007, International Conference on Semantic Computing (ICSC 2007).

[18]  Chin-Hui Lee,et al.  Boosting of Maximal Figure of Merit Classifiers for Automatic Image Annotation , 2007, 2007 IEEE International Conference on Image Processing.

[19]  Aaron Sloman,et al.  AN ALTERNATIVE TO WORKING ON MACHINE CONSCIOUSNESS , 2010 .

[20]  T. Landauer,et al.  A Solution to Plato's Problem: The Latent Semantic Analysis Theory of Acquisition, Induction, and Representation of Knowledge. , 1997 .

[21]  J. Gregory Trafton,et al.  Enabling effective human-robot interaction using perspective-taking in robots , 2005, IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans.

[22]  Alex Pentland,et al.  Human Computing and Machine Understanding of Human Behavior: A Survey , 2007, Artifical Intelligence for Human Computing.