Dance Step Estimation Method Based on HMM for Dance Partner Robot
Dance Step Estimation Method Based on HMM for Dance Partner Robot
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DOI：
10.1109/tie.2007.891642
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发表时间：
2007-03
影响因子：
7.7
通讯作者：
T. Takeda;Y. Hirata;K. Kosuge
中科院分区：
文献类型：
--
作者：
T. Takeda;Y. Hirata;K. Kosuge
本文的主要目的是通过物理交互实现有效的人机协调。有人提出了一个舞伴机器人作为其平台。要实现人机的有效协调，识别人类意图将是关键问题之一。本文重点研究一种舞步估计方法，该方法估计人类想要的下一个舞步。在估计舞步时，使用人类施加给机器人的力/力矩的时间序列数据。舞蹈中测量的力/力矩的时间序列数据包括不确定性，例如时间滞后和重复试验的变化，因为人类不能总是精确地向机器人施加相同的力/力矩。为了处理包含这种不确定性的时间序列数据，利用隐马尔可夫模型设计舞步估计方法。通过所提出的方法，机器人成功地根据人类意图估计了下一个舞步
The main purpose of this paper is to realize an effective human-robot coordination with physical interaction. A dance partner robot has been proposed as a platform for it. To realize the effective human-robot coordination, recognizing human intention would be one of the key issues. This paper focuses on an estimation method for dance steps, which estimates a next dance step intended by a human. In estimating the dance step, time series data of force/moment applied by the human to the robot are used. The time series data of force/moment measured in dancing include uncertainty such as time lag and variations for repeated trials because the human could not always exactly apply the same force/moment to the robot. In order to treat the time series data including such uncertainty, hidden Markov models are utilized for designing the dance step estimation method. With the proposed method, the robot successfully estimates a next dance step based on human intention