| Texto completo | |
| Autor(es): |
Tozadore, Daniel C.
;
Romero, Roseli A. F.
;
ACM
Número total de Autores: 3
|
| Tipo de documento: | Artigo Científico |
| Fonte: | COMPANION PUBLICATON OF THE 2020 INTERNATIONAL CONFERENCE ON MULTIMODAL INTERACTION (ICMI '20 COMPANION); v. N/A, p. 8-pg., 2020-01-01. |
| Resumo | |
Social robots' contributions to education are notorious but, in times, limited by the difficulty in their programming by regular teachers. Our framework named R-CASTLE aims to overcome this problem by providing the teachers with an easy way to program their content and the robot's behavior through a graphical interface. However, the robot's behavior adaptation algorithm maybe still not the best intuitive method for teachers' understanding. Fuzzy systems have the advantage of being modeled in a more human-like way than other methods due to their implementation based on linguistic variables and terms. Thus, fuzzy modeling for robot behavior adaptation in educational children-robot interactions is proposed for this framework. The modeling resulted in an adaptation algorithm that considers a multimodal and autonomous assessment of the students' skills: attention, communication, and learning. Furthermore, preliminary experiments were performed considering videos with the robot in a school environment. The adaptation was set to change the content approach difficulty to produce a suitably challenging behavior according to each students' reactions. Results were compared to a Rule-Based adaptive method. The fuzzy modeling showed similar accuracy to the ruled-based method with a suggestion of a more intuitive interpretation of the process. (AU) | |
| Processo FAPESP: | 14/50851-0 - INCT 2014: Instituto Nacional de Ciência e Tecnologia para Sistemas Autônomos Cooperativos Aplicados em Segurança e Meio Ambiente |
| Beneficiário: | Marco Henrique Terra |
| Modalidade de apoio: | Auxílio à Pesquisa - Temático |