Human-robot interaction by reading human intention based on mirror-neuron system

Abstract

Considering the human-robot symbiosis in coming years, robots should be able to read human intention for natural and rational interaction with human beings. This paper proposes effective human-robot interaction (HRI) by reading the human intention using cognitive architecture. Proposed intention reading algorithm is inspired by mirror-neuron system and simulation theory which are the significant parts of human mind reading skill. For human intention reading, the cognitive architecture consisting of eight modules, i.e. perception, attention, behavior mapping, behavior model, intention reading, memory, behavior selection, and actuator modules is also proposed. The effectiveness of the proposed scheme is demonstrated through computer simulations on human-robot play with two different objects, such as a ball and a toy car.