Knowledge model-based adaptive intelligent control of robots for a symbiotic human–robot system
by Tao Zhang, Haruki Ueno
International Journal of Automation and Control (IJAAC), Vol. 1, No. 1, 2007

Abstract: 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.

Online publication date: Thu, 19-Apr-2007

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