Robot dan Manusia
Social Constraints On Animate Vision PDF Print E-mail
Written by Rizki Noor Hidayat Wijayaź   

Cynthia Breazeal, Aaron Edsinger, Paul Fitzpatrick, and Brian Scassellati Massachusetts Institute of Technology, Cambridge MA 02139, USA, fcynthia,edsinger,paulfitz, ,

Abstract.

In 1991, Ballard [2] described the implications of having a visual system that could actively position the camera coordinates in response to physical stimuli. In humanoid robotic systems, or in any animate vision system that interacts with people, social dynamics provide additional levels of constraint and provide additional opportunities for processing economy. In this paper, we describe an integrated visual-motor system that has been implemented on a humanoid robot to negotiate the robot*s physical constraints, the perceptual needs of the robot*s behavioral and motivational systems, and the social implications of motor acts.

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Discriminating Animate From Inanimate Visual Stimuli PDF Print E-mail
Written by Rizki Noor Hidayat Wijayaź   

Brian Scassellati MIT Artificial Intelligence Laboratory 200 Technology Square Cambridge, MA 02139

Abstract

From as early as 6 months of age, human children distinguish between motion patterns generated by animate objects from patterns generated by moving inanimate objects, even when the only stimulus that the child observes is a single point of light moving against a blank background. The mechanisms by which the animate/inanimate distinction are made are unknown, but have been shown to rely only upon the spatial and temporal properties of the movement. In this paper, I present both a multiagent architecture that performs this classification as well as detailed comparisons of the individual agent contributions against human baselines.

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How To Build Robots That Make Friends And Influence People PDF Print E-mail
Written by Rizki Noor Hidayat Wijayaź   

Cynthia Breazeal Brian Scassellati MIT Artificial Intelligence Lab 545 Technology Square Cambridge, MA 02139

Abstract

In order to interact socially with a human, a robot must convey intentionality, that is, the human must believe that the robot has beliefs, desires, and intentions. We have constructed a robot which exploits natural human social tendencies to convey intentionality through motor actions and facial expressions. We present results on the integration of perception, attention, motivation, behavior, and motor systems which allow the robot to engage in infant-like interactions with a human caregiver.

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Towards Manipulation-driven Vision PDF Print E-mail
Written by Rizki Noor Hidayat Wijayaź   

Paul M. Fitzpatrick MIT AI Lab Massachussetts Institute of Technology USA and Giorgio Metta; Lira Lab, DIST University of Genova Italy

Abstract

For the purposes of manipulation, we would like to know what parts of the environment are physically coherent ensembles { that is, which parts will move together, and which are more or less independent. It takes a great deal of experience before this judgement can be made from purely visual information. This paper develops active strategies for acquiring that ex- perience through experimental manipulation, using tight correlations between arm motion and optic flow to detect both the arm itself and the boundaries of objects with which it comes into contact.

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Recognizing And Remembering Individuals:online And Unsupervised Face Recognition For Humanoid Robot PDF Print E-mail
Written by Rizki Noor Hidayat Wijayaź   

Lijin Aryananda Artificial Intelligence Laboratory, MIT, Cambridge, MA, USA,

Abstract

Individual recognition is a widely reported phenomenon in the animal world, where it contributes to successful maternal interaction, parental care, group breeding, cooperation, mate choice, etc. This work addresses the question of how one may implement such social competence in a humanoid robot. We argue that the robot must be able to recognize people and learn about their various characteristics through embodied social interaction and thus proposed an initial implementation of an online and unsupervised face recognition system for Kismet, our sociable robotic platform. We show how specific features of this particular application drove our decision and implementation process, challenged by the difficulty of the face recognition problem, which has so far been explored in the supervised manner. Experimental results are reported to illustrate what was solved and lessons learned from the current implementation.

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