Papers

16

Total Citations

263

H-Index

9

About

Yuichi Motai is a prominent robotics and computer vision researcher whose work spans robotic perception, human-robot interaction, autonomous navigation, and intelligent sensing systems. Over two decades of sustained contribution, his research has fundamentally advanced how robots see, learn, and interact with their environments. Motai's most influential work centers on hand-eye calibration for robotic vision, with his 2008 paper on viewpoint selection garnering 65 citations and establishing a foundational methodology for precise sensor calibration in active object grasping and control. His early contributions also include pioneering predictive fuzzy logic controllers for mobile robots navigating nonholonomic constraints, work that addressed real-world challenges like time delays and nonlinear dynamics in autonomous navigation. Beyond classical robotics, Motai has made significant strides in thermal and multisensor fusion, developing human behavior-based tracking systems using omni-directional infrared cameras—critical technologies for unmanned and collaborative robotic systems. His research in visual perception for human-robot interaction further demonstrates his commitment to practical, intelligent robotic systems capable of interpreting complex human behavior. With over 230 cumulative citations across his top works, Motai's research has meaningfully shaped the fields of robotic vision and intelligent autonomous systems, making his publications essential reading for researchers working at the intersection of machine perception and robotics.

Research Focus

Key Achievements

9
H-Index
16
Papers
263
Total Citations
16
Avg Citations/Paper
🏆 Most Cited Paper
Hand–Eye Calibration Applied to Viewpoint Selection for Robotic Vision
65 citations · 2008
📈 Most Prolific Year: 2005 (3 Papers)
🤝 Key Collaborators: 16
🏛 Institutions: University of Vermont, Virginia Commonwealth University, Purdue University West Lafayette

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
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