About

Kenichi Ohara is a robotics researcher whose work spans human-robot interaction, autonomous navigation, bipedal locomotion, and robot psychology. His research is distinguished by its ambition to make robots genuinely compatible with human social environments — not merely functional, but socially intelligent. Ohara's most influential contributions center on social navigation and collision avoidance. His modified Social Force Model, which incorporates body pose and face orientation to anticipate human movement, has garnered 54 citations and represents a meaningful advance in how robots interpret human intent in shared spaces. A companion paper on social navigation using face orientation further cemented this approach with 33 citations. Equally notable is his sustained investigation into how humans psychologically perceive humanoid robots. Through the development of evaluation instruments such as PERNOD and related scales, and through direct comparisons of virtual and real humanoids, Ohara has helped establish a rigorous empirical foundation for robot-oriented psychology — work collectively drawing over 90 citations. His technical breadth is evident in contributions to bipedal rough-terrain walking using ZMP criteria maps, ubiquitous robot localization, vision-based dismantling robotics, and real-time trajectory planning for mobile manipulators. Together, these works position Ohara as a versatile researcher bridging the mechanical and social dimensions of robotics.

Research Focus

Key Achievements

14
H-Index
70
Papers
668
Total Citations
10
Avg Citations/Paper
🏆 Most Cited Paper
HUMAN–ROBOT COLLISION AVOIDANCE USING A MODIFIED SOCIAL FORCE MODEL WITH BODY POSE AND FACE ORIENTATION
54 citations · 2013
📈 Most Prolific Year: 2009 (12 Papers)
🤝 Key Collaborators: 114
🏛 Institutions: The University of Osaka, National Institute of Advanced Industrial Science and Technology, Meijo University, University of Tsukuba, Shibaura Institute of Technology, National Institute of Biomedical Innovation, Health and Nutrition

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 34 days ago