RT Journal Article
T1 A Bio-inspired Motivational Decision Making System for Social Robots Based on the Perception of the User
A1 Maroto Gómez, Marcos
A1 Castro González, Álvaro
A1 Castillo Montoya, José Carlos
A1 Malfaz Vázquez, María Ángeles
A1 Salichs Sánchez-Caballero, Miguel
AB Nowadays, many robotic applications require robots making their own decisions and adapting to different conditions and users. This work presents a biologically inspired decision making system, based on drives, motivations, wellbeing, and self-learning, that governs the behavior of the robot considering both internal and external circumstances. In this paper we state the biological foundations that drove the design of the system, as well as how it has been implemented in a real robot. Following a homeostatic approach, the ultimate goal of the robot is to keep its wellbeing as high as possible. In order to achieve this goal, our decision making system uses learning mechanisms to assess the best action to execute at any moment. Considering that the proposed system has been implemented in a real social robot, human-robot interaction is of paramount importance and the learned behaviors of the robot are oriented to foster the interactions with the user. The operation of the system is shown in a scenario where the robot Mini plays games with a user. In this context, we have included a robust user detection mechanism tailored for short distance interactions. After the learning phase, the robot has learned how to lead the user to interact with it in a natural way.
PB MDPI
SN 1424-8220
YR 2018
FD 2018-08-16
LK https://hdl.handle.net/10016/28021
UL https://hdl.handle.net/10016/28021
LA eng
NO The research leading to these results has received funding from the projects: Development of social robots to help seniors with cognitive impairment (ROBSEN), funded by the Ministerio de Economia y Competitividad; and RoboCity2030-III-CM, funded by Comunidad de Madrid and cofunded by Structural Funds of the EU.
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RD 13 ago. 2024