Dance step estimation method based on HMM for dance partner robot

Takahiro Takeda, Yasuhisa Hirata, Kazuhiro Kosuge

Research output: Contribution to journalArticlepeer-review

77 Citations (Scopus)


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.

Original languageEnglish
Pages (from-to)699-706
Number of pages8
JournalIEEE Transactions on Industrial Electronics
Issue number2
Publication statusPublished - 2007 Apr


  • Ballroom dances
  • Dance step estimation
  • Hidden Markov models (HMMs)
  • Human intention
  • Human-robot cooperation
  • Mobile robot

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Electrical and Electronic Engineering


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