SciELO - Scientific Electronic Library Online

vol.18 issue2Detecção e classificação de faltas a partir da análise de registros oscilográficos via redes neurais artificiais e transformada waveletRobótica cognitiva: programação baseada em lógica para controle de robôs author indexsubject indexarticles search
Home Pagealphabetic serial listing  

Services on Demand




Related links


Sba: Controle & Automação Sociedade Brasileira de Automatica

Print version ISSN 0103-1759


SELVATICI, Antonio Henrique Pinto  and  COSTA, Anna Helena Reali. Aprendizado da coordenação de comportamentos primitivos para robôs móveis. Sba Controle & Automação [online]. 2007, vol.18, n.2, pp.173-186. ISSN 0103-1759.

In most real world applications, mobile robots should perform their tasks in previously unknown environments. Thus, a mobile robot architecture capable of adaptation is very suitable. This work presents an adaptive architecture for mobile robots, AAREACT, which has the ability of learning how to coordinate primitive behaviors codified by the Potential Fields method by using Reinforcement Learning. The proposed architecture’s performance is compared to that showed by an architecture that performs a fixed coordination of its behaviors, and shows a better performance for different environments. Experiments were performed in the robot Pioneer’s simulator, from ActivMedia Robotics®. The obtained results also suggest that AAREACT has good adaptation skills for specific environment and task.

Keywords : Mobile robotics; control architecture; reactive behaviors; reinforcement learning.

        · abstract in Portuguese     · text in Portuguese     · Portuguese ( pdf epdf )


Creative Commons License All the contents of this journal, except where otherwise noted, is licensed under a Creative Commons Attribution License