Improvement of an architecture for social robotics

Author(s)

Renato Ramos da Silva

• Document type: Doctoral Thesis
• Press: São Carlos.
• Institution: Universidade de São Paulo (USP). Instituto de Ciências Matemáticas e de Computação (ICMC/SB)
• Defense date: 2013-02-07

Examining board members

Roseli Aparecida Francelin Romero; Glauco Augusto de Paula Caurin; Seiji Isotani; Maria de Jesus Dutra dos Reis; Francisco Aparecido Rodrigues

• Advisor: Roseli Aparecida Francelin Romero

Abstract

One important aspect of human interaction is the shared attention. It is a communication process where one person redirect his or her attention to an object or event and the other person or people follow gaze to the same place. This process end with a pointing and a comment about the situation by the person that follows the attention. This important ability was learned by us during the childhood and some roboticist are trying to develop robotics architectures to learn this ability in robots. In this way, the Learning Lab Robotics has been working on a robotic architecture used with this proposed. It is composed by three modules, stimulus perception, consequence control and response emission. This robotic architecture was evaluated to control a robotic head and it was capable to learn to follow gaze and identify some objects. However, all of these modules have some limitations. In order to take a better interaction between a robot and a human and reduce the effects of limitations, some improvements were developed. They include a new head pose classification algorithm using histogram of oriented gradient, increase the capability of consequence control with new reflexes and new learning algorithms to select the best action. All modification reduce the limitations and it can improve the interactions between a robot and a human being (AU)

• FAPESP's process: 08/09744-4 - Learning Methods for Human-Robot Interaction
• Grantee: Renato Ramos da Silva
• Support Opportunities: Scholarships in Brazil - Doctorate