Affective visuomotor interaction: a functional model for socially competent robot grasping

Chinallato, Eris ORCID logoORCID: https://orcid.org/0000-0003-1920-2238, Ferretti, Gabriele and Irving, Lucy ORCID logoORCID: https://orcid.org/0000-0001-6411-1488 (2019) Affective visuomotor interaction: a functional model for socially competent robot grasping. Martinez-Hernandez, Uriel, Vouloutsi, Vasiliki, Mura, Anna, Mangan, Michael, Minoru, Asada, Prescott, Tony J. and Verschure, Paul F. M. J., eds. Living Machines 2019. Lecture Notes in Computer Science (LNCS, vol 11556). In: 8th International Conference, Living Machines 2019, 09-12 Jul 2019, Nara, Japan. ISBN 9783030247409, e-ISBN 9783030247416. ISSN 0302-9743 [Conference or Workshop Item] (doi:10.1007/978-3-030-24741-6_5)

[img]
Preview
PDF - Final accepted version (with author's formatting)
Download (444kB) | Preview

Abstract

In the context of human-robot social interactions, the ability of interpreting the emotional value of objects and actions is critical if we wish robots to achieve truly meaningful interchanges with human partners. We review here the most significant findings related to reward management and values assignment in the primate brain, with particular regard to the prefrontal cortex. Based on such findings, we propose a novel model of vision-based grasping in which the context-dependent emotional value of available options (e.g. damageable or dangerous items) is taken into account when interacting with objects in the real world. The model is both biologically plausible and suitable for being applied to a robotic setup. We provide a testing framework along with implementation guidelines.

Item Type: Conference or Workshop Item (Paper)
Additional Information: Paper published as:
Chinellato E., Ferretti G., Irving L. (2019) Affective Visuomotor Interaction: A Functional Model for Socially Competent Robot Grasping. In: Martinez-Hernandez U. et al. (eds) Biomimetic and Biohybrid Systems. Living Machines 2019. Lecture Notes in Computer Science, vol 11556. Springer, Cham.
Research Areas: A. > School of Science and Technology
Item ID: 28858
Notes on copyright: The final authenticated version is available online at https://doi.org/10.1007/978-3-030-24741-6_5.
Useful Links:
Depositing User: Lucy Irving
Date Deposited: 27 Jan 2020 13:44
Last Modified: 29 Nov 2022 18:57
URI: https://eprints.mdx.ac.uk/id/eprint/28858

Actions (login required)

View Item View Item

Statistics

Activity Overview
6 month trend
155Downloads
6 month trend
117Hits

Additional statistics are available via IRStats2.