Towards an open-source social middleware for humanoid robots

Recent examples of robotics middleware including YARP, ROS, and NaoQi, have greatly enhanced the standardisation, interoperability and rapid development of robotics application software. In this paper, we present our research towards an open source middleware to support the development of social robotic applications. In the core of the ability of a robot to interact socially are algorithms to perceive the actions and intentions of a human user. We attempt to provide a computational layer to standardise these algorithms utilising a bioinspired computational architecture known as HAMMER (Hierarchical Attentive Multiple Models for Execution and Recognition) and demonstrate the deployment of such layer on two different humanoid platforms, the Nao and iCub robots. We use a dance interaction scenario to demonstrate the utility of the framework.