HRI Design Research for Intelligent Household Service Robots: Teler as a Case Study
This paper analyzes the human-robot interaction (HRI) design based on artificial intelligence technology. Combined with the needs of artificial intelligence technology, this paper summed up the new characteristics of human-robot interaction which include high dimension, high tolerance, complex scenario merged with context awareness computing, consciousness awareness computing and emotion awareness computing. Take Teler, a household robot of Robotics Interaction Lab in Intel Labs China as the reference case, the paper analyzes the methods and characteristics of household robotics human-computer interaction. Multi-channel information input portal, parallel interactive framework and multi-sensory collaborative feedback are the new interaction design requirements. The paper summarizes the advantage and disadvantages of robot-human interaction in artificial intelligence field, sorts out information classification and information processing. In this paper, we present three human-robot interactive relationships which include passive feedback, proactive learning and active feedforward, and maps the three relationships with accurate command interaction, semi-opening dialog interaction and opening dialog system interaction. The three types of HRI associate with the different mental model, interaction model, information architecture, interactive behavior logic, information visualization and interface design. The paper presents the new method of interaction design for household robot context-awareness interaction and use the case Teler AI household service robot human-robot interaction design to verify the user experience targets and usability targets.
KeywordsHRI Artificial intelligence Household service robots Interaction design Information design
The intelligent household service robot Teler is a research project supported by Intel Labs China. We accomplish the HRI design with programmers, mechanical designers and other colleagues in Robot Interaction Lab in 2017. Dr. Peng Wang, Xiaobo Hu and all the research team members are greatly appreciated for the big data computing and human-robot interaction technology.
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