A Robot that Counts Like a Child - a Developmental Model of Counting and Pointing

PECYNA, Leszek, CANGELOSI, Angelo and DI NUOVO, Alessandro (2020). A Robot that Counts Like a Child - a Developmental Model of Counting and Pointing. Psychological Research: an international journal of perception, attention, memory and action.

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Abstract

In this paper, a novel neuro-robotics model capable of counting real items is introduced. The model allows us to investigate the interaction between embodiment and numerical cognition. This is composed of a deep neural network capable of image processing and sequential tasks performance, and a robotic platform providing the embodiment—the iCub humanoid robot. The network is trained using images from the robot’s cameras and proprioceptive signals from its joints. The trained model is able to count a set of items and at the same time points to them. We investigate the influence of pointing on the counting process and compare our results with those from studies with children. Several training approaches are presented in this paper, all of them use pre-training routine allowing the network to gain the ability of pointing and number recitation (from 1 to 10) prior to counting training. The impact of the counted set size and distance to the objects are investigated. The obtained results on counting performance show similarities with those from human studies.

Item Type:	Article
Uncontrolled Keywords:	Experimental Psychology; 1701 Psychology; 1702 Cognitive Sciences
Identification Number:	https://doi.org/10.1007/s00426-020-01428-8
SWORD Depositor:	Symplectic Elements
Depositing User:	Symplectic Elements
Date Deposited:	21 Oct 2020 11:33
Last Modified:	16 Feb 2022 16:10
URI:	https://shura.shu.ac.uk/id/eprint/27482

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