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Issue title: Intelligent and Fuzzy Systems applied to Language & Knowledge Engineering
Guest editors: David Pinto, Vivek Kumar Singh, Aline Villavicencio, Philipp Mayr-Schlegel and Efstathios Stamatatos
Article type: Research Article
Authors: Pineda, Luis A.a; * | Rodríguez, Arturob | Fuentes, Gibrána | Hernández, Noéa | Reyes, Mauriciob; c | Rascón, Caleba; d | Cruz, Ricardob | Vélez, Ivetteb | Ortega, Hernandoe
Affiliations: [a] Departamento de Ciencias de la Computación, Instituto de Investigaciones en Matemáticas Aplicadas y en Sistemas (IIMAS), Universidad Nacional Autónoma de México (UNAM) | [b] Posgrado en Ciencia e Ingeniería de la Computación, Universidad Nacional Autónoma de México (UNAM) | [c] Centro de Investigaciones en Diseño Industrial (CIDI), Facultad de Arquitectura, Universidad Nacional Autónoma de México (UNAM) | [d] Consejo Nacional de Ciencia y Tecnología (CONACyT), México | [e] Departamento de Probabilidad y Estadística, Instituto de Investigaciones en Matemáticas Aplicadas y en Sistemas (IIMAS), Universidad Nacional Autónoma de México (UNAM)
Correspondence: [*] Corresponding author. Luis A. Pineda, Departamento de Ciencias de la Computación, Instituto de Investigaciones en Matemáticas Aplicadas y en Sistemas (IIMAS), Universidad Nacional Autónoma de México (UNAM). E-mail: [email protected].
Abstract: In this paper a strategy for incorporating a flexible and reliable high-level inference module in service robots is presented. This module is a part of the robot’s cognitive architecture which coordinates perception, inference and action within the robot’s communication and interaction cycle. The present approach relies on an explicit representation of the structure of the task performed by the robot. There are three kinds of inferences that the robot can use opportunistically along the task: (1) diagnosis, (2) decision making and (3) planning; each kind can be used in specific situations of the task structure or performed in arbitrary situations with recovery purposes when there is an interaction failure. In this latter case the three kinds of inference are performed sequentially in what we call the daily-life inference cycle. The inference cycle allows the incorporation of basic emotions in the robot’s behavior. A case study incorporating these functionalities in the robot Golem-III is presented. The paper is concluded with a reflection on the opportunistic use of inference schemes to support flexible and robust behavior, including the expression of emotions, in service robots.
Keywords: Inference in service robots, robust behavior in service robots, robotics cognitive architecture, the Golem-III robot
DOI: 10.3233/JIFS-169512
Journal: Journal of Intelligent & Fuzzy Systems, vol. 34, no. 5, pp. 3301-3311, 2018
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