Abstract
In this paper, we establish a time-varying fuzzy Markov model to estimate human intention for natural non-verbal human robot interface. Based on human posture information, we change the probability between states to improve the accuracy of estimation of human intention. The advantages of the approach are three fold: i) non-verbal information is core of natural interaction; ii) time-varying probability improves estimation accuracy; and iii) fuzzy inference consider practical human experience.
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Liu, P., Yang, CE. (2012). Human Intention Estimation Using Time-Varying Fuzzy Markov Models for Natural Non-verbal Human Robot Interface. In: Su, CY., Rakheja, S., Liu, H. (eds) Intelligent Robotics and Applications. ICIRA 2012. Lecture Notes in Computer Science(), vol 7507. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33515-0_20
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DOI: https://doi.org/10.1007/978-3-642-33515-0_20
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