TY - GEN
T1 - Design and Implementation of Telemarketing Robot with Emotion Identification for Human-Robot Interaction
AU - Arce, Diego
AU - Balbuena, Jose
AU - Menacho, Daniel
AU - Caballero, Luis
AU - Cisneros, Enzo
AU - Huanca, Dario
AU - Alvites, Marcelo
AU - Beltran, Cesar
AU - Cuellar, Francisco
N1 - Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - This work presents the design, development and preliminary tests of an innovative mobile robot which interact with humans for marketing, advertising and customer services. The proposed robot can be use for various activities related to human-robot interaction (conferences, plant visits, marketing, advertising, supervision). The robot has multiple sensors in order to evaluate the personal space of customers. It also includes display touch screens in order to achieve an emphatic interaction and provide personalized attention. An emotion classification algorithm was implemented aiming to analyze how the customer reacts to the advertisements that appear on the screens, and modify its response accordingly. The robot functionalities and interaction capabilities were validated using a prototype. The results demonstrate a good assessment regarding reliability, usability and performance, and measured a positive emotional response from the participants.
AB - This work presents the design, development and preliminary tests of an innovative mobile robot which interact with humans for marketing, advertising and customer services. The proposed robot can be use for various activities related to human-robot interaction (conferences, plant visits, marketing, advertising, supervision). The robot has multiple sensors in order to evaluate the personal space of customers. It also includes display touch screens in order to achieve an emphatic interaction and provide personalized attention. An emotion classification algorithm was implemented aiming to analyze how the customer reacts to the advertisements that appear on the screens, and modify its response accordingly. The robot functionalities and interaction capabilities were validated using a prototype. The results demonstrate a good assessment regarding reliability, usability and performance, and measured a positive emotional response from the participants.
KW - Human-robot interaction
KW - deep learning
KW - emotion classification
KW - mobile robot
UR - http://www.scopus.com/inward/record.url?scp=85147552340&partnerID=8YFLogxK
U2 - 10.1109/IRC55401.2022.00037
DO - 10.1109/IRC55401.2022.00037
M3 - Conference contribution
AN - SCOPUS:85147552340
T3 - Proceedings - 2022 6th IEEE International Conference on Robotic Computing, IRC 2022
SP - 177
EP - 180
BT - Proceedings - 2022 6th IEEE International Conference on Robotic Computing, IRC 2022
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 6th IEEE International Conference on Robotic Computing, IRC 2022
Y2 - 5 December 2022 through 7 December 2022
ER -