Robotic Architecture Inspired on Behavior Analysis

Abstract

Social robots are embodied agents that are part of a heterogeneous group: a society of robots or humans. They are able to recognize human beings and each other, and engage in social interactions. They possess histories and they explicitly communicate and learn from interactions. The construction of social robots may strongly benefit from using a robotic architecture. However, a robotic architecture for sociable robots must have structures and mechanism to allow social interaction control and learning from environment. In this paper, we propose a robotic architecture inspired on Behavior Analysis. Methods and structures of the proposed architecture are presented and discussed. The architecture was evaluated on a Skinner Box simulator and the obtained results shown that the architecture is able to produce appropriate behavior and to learn from social interaction.