Multimodal Child-Robot Interaction: Building Social Bonds

For robots to interact effectively with human users they must be capable of coordinated, timely behavior in response to social context. The Adaptive Strategies for Sustainable Long-Term Social Interaction (ALIZ-E) project focuses on the design of long-term, adaptive social interaction between robots and child users in real-world settings. In this paper, we report on the iterative approach taken to scientific and technical developments toward this goal: advancing individual technical competen- cies and integrating them to form an autonomous robotic system for evaluation "in the wild." The first evaluation iterations have shown the potential of this methodology in terms of adaptation of the robot to the interactant and the resulting influences on engagement. This sets the foundation for an ongoing research program that seeks to develop technologies for social robot companions.

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Tony Belpaeme
Paul Baxter
Robin Read
Rachel Wood Heriberto Cuayahuitl
Bernd Kiefer
Stefania Racioppa
Ivana Kruijff-Korbayov?a Georgios Athanasopoulos
Valentin Enescu Rosemarijn Looije
Mark Neerincx Yiannis Demiris
Raquel Ros-Espinoza Aryel Beck
Lola Canamero
Antione Hiolle
Matthew Lewis Ilaria Baroni
Marco Nalin Piero Cosi
Giulio Paci
Fabio Tesser
Giacomo Sommavilla Remi Humbert
Michael A. Goodrich - Managing Editor - Brigham Young University, Provo, Utah 84602, Stati Uniti, Stati Uniti d'America
Journal of Human-Robot Interaction 1 (2012): 33–53.
info:cnr-pdr/source/autori:Tony Belpaeme, Paul Baxter, Robin Read, Rachel Wood Heriberto Cuayahuitl, Bernd Kiefer, Stefania Racioppa, Ivana Kruijff-Korbayov?a Georgios Athanasopoulos, Valentin Enescu Rosemarijn Looije, Mark Neerincx Yiannis Demiris, Raque
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