Knowledge model-based adaptive intelligent control of robots for a symbiotic human-robot system

This paper proposes a novel knowledge model-based adaptive intelligent control of robots for a symbiotic human-robot system. In this method, a knowledge model is first defined by the frame-based knowledge representation. It contains various frames for describing different users, features of multiple robots as well as robot behaviours for human-robot interaction and performing various tasks. According to this knowledge model, the intelligent control of robots in a symbiotic human-robot system can be implemented by means of a software platform, called Software Platform for Agents and Knowledge Management (SPAK). In addition, a kind of learning function is developed and integrated into the SPAK in order that the system can autonomously learn new knowledge by human-robot interaction and generate new control strategy for robots. Hence, the symbiotic human-robot system can adapt to various situations with different human requests and realise high-autonomous intelligent control of robots. In this paper, the effectiveness of the proposed method is verified by the experiment using actual robots.