Papers
107
Total Citations
1,905
H-Index
20
About
Kosuke Sekiyama is a prominent robotics researcher whose work spans autonomous systems, human-robot collaboration, and assistive technologies. He has made foundational contributions to the control of underactuated mechanical systems, most notably through his highly cited work on sliding-mode velocity control for mobile-wheeled inverted-pendulum systems (241 citations), which has become a key reference in autonomous robotics and intelligent vehicle research. Sekiyama has also pioneered approaches to odor source localization, developing particle swarm optimization (PSO)-based mobile sensor networks and biologically inspired odor-gated rheotaxis models to navigate dynamic, obstacle-rich environments — work that has attracted over 180 citations and advanced the field of environmental sensing robotics. His research extends meaningfully into human-robot collaborative manufacturing, where he introduced innovative subtask allocation frameworks for hybrid assembly systems (157 citations), directly improving the efficiency and flexibility of modern production environments. Sekiyama has equally distinguished himself in assistive robotics, developing intelligent walking-aid cane robots for fall detection and prevention among elderly users. His contributions to 3-D biped walking algorithms and multi-locomotion robotic systems further demonstrate remarkable breadth. Together, his body of work — accumulating nearly 1,000 citations — reflects a sustained commitment to making robotics safer, smarter, and more responsive to human needs.
Research Focus
Key Achievements
Top Papers
- 1Sliding-Mode Velocity Control of Mobile-Wheeled Inverted-Pendulum Systems241 citations · 2010
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- 4Fall Detection and Prevention Control Using Walking-Aid Cane Robot104 citations · 2015
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- 8Multi-Locomotion Robotic Systems46 citations · 2012
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- 10Study of Fall Detection Using Intelligent Cane Based on Sensor Fusion36 citations · 2008