文章基本信息

标题：Innovative Internet of Things-reinforced Human Recognition for Human-Machine Interaction Purposes
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作者：Arkadiusz Gardecki ; Michal Podpora ; Aleksandra Kawala-Janik 等
期刊名称：IFAC PapersOnLine
印刷版ISSN：2405-8963
出版年度：2018
卷号：51
期号：6
页码：138-143
DOI：10.1016/j.ifacol.2018.07.143
语种：English
出版社：Elsevier
摘要：AbstractAccurate and reliable human recognition and parametrisation have always been an important challenge in efficient Man-Machine Interaction. A humanoid robot is able to offer a much richer and more natural behaviour and human-like communication, but only if the robot possesses sufficient knowledge about the interlocutor, such as inter alia: gender, age, mood, behaviour data, interaction history. In this paper authors introduced an innovative conception in Human-Machine Interaction, where instead of thinking about an interaction as an event (which uses and produces information) an innovative point of view was proposed, where the interaction is just an event in a continuous flow of information. The difference, once perceived, results in an astounding change of conception, as well as a whole new set of ideas. The human detection, information acquisition, human recognition – can be performed earlier, before a human reaches the humanoid robot, also the history of interactions and possible interests of the interlocutor can be predicted before they would even start the conversation. This paper contains a detailed analysis of the proposed environment-based approach to interaction, as well as the Internet of Things-reinforced information acquisition.
关键词：KeywordsHuman-Machine InteractionInternet of ThingsHuman RecognitionHumanoid RobotsHuman Identification