TY  - EJOU
AU  - Han, Hasan 
AU  - Karadeniz, Oguzcan 
AU  - Dalyan, Tugba 
AU  - Sonmez, Elena Battini 
AU  - Sarioglu, Baykal 

TI  - Acknowledge of Emotions for Improving Student-Robot Interaction
T2  - Intelligent Automation \& Soft Computing

PY  - 2023
VL  - 37
IS  - 1
SN  - 2326-005X

AB  - Robot companions will soon be part of our everyday life and students in the engineering faculty must be trained to design, build, and interact with them. The two affordable robots presented in this paper have been designed and constructed by two undergraduate students; one artificial agent is based on the Nvidia Jetson Nano development board and the other one on a remote computer system. Moreover, the robots have been refined with an empathetic system, to make them more user-friendly. Since automatic facial expression recognition skills is a necessary pre-processing step for acknowledging emotions, this paper tested different variations of Convolutional Neural Networks (CNN) to detect the six facial expressions plus the neutral face. The state-of-the-art performance of 75.1% on the Facial Expression Recognition (FER) 2013 database has been reached by the ensemble voting method. The runner-up model is the Visual Geometry Group (VGG) 16 which has been adopted by the two robots to recognize the expressions of the human partner and behave accordingly. An empirical study run among 55 university students confirmed the hypothesis that contact with empathetic artificial agents contributes to increasing the acceptance rate of robots
KW  - Artificial intelligence; deep learning; convolutional neural networks; facial expression recognition; robotics; education; professional learning

DO  - 10.32604/iasc.2023.030674