Papers

16

Total Citations

285

H-Index

10

About

Takahiro Takeda is a pioneering robotics researcher whose work centers on human-robot coordination through physical interaction, with a particular focus on dance partner robots. His most significant contribution is the development of the "MS DanceR" (Mobile Smart Dance Robot) and "PBDR" (Partner Ballroom Dance Robot) platforms, which can dance with human partners by estimating their intended next steps using Hidden Markov Models (HMMs) and neural networks. His seminal 2007 paper on HMM-based dance step estimation has garnered 103 citations, establishing the foundation for this field. Takeda’s research addresses key challenges in human-robot interaction, including error recovery in step selection and cooperative motion generation with adjustable stride length. Beyond dance robotics, he has contributed to humanoid robot locomotion and stability control, notably in soccer-playing robots (EROS), and has explored energy-efficient walking using evolutionary algorithms. His work extends to practical applications such as route planning for disaster waste disposal using robot technology. With over 240 total citations across his most-cited papers, Takeda’s research has significantly advanced the understanding of how robots can anticipate and respond to human intentions in physically interactive settings, making him a notable figure in the field of social and partner robotics.

Research Focus

Key Achievements

10
H-Index
16
Papers
285
Total Citations
18
Avg Citations/Paper
🏆 Most Cited Paper
Dance Step Estimation Method Based on HMM for Dance Partner Robot
103 citations · 2007
📈 Most Prolific Year: 2007 (4 Papers)
🤝 Key Collaborators: 30
🏛 Institutions: Tohoku University, Tokyo Metropolitan University, Daiichi Institute of Technology

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago