Papers
38
Total Citations
468
H-Index
9
About
Naoki Motoi is a prominent robotics researcher whose work spans mobile robot navigation, humanoid locomotion, and motion control systems. His research has made significant contributions to autonomous robot navigation, particularly through innovative extensions of the Dynamic Window Approach (DWA) for local path planning. His 2022 paper introducing virtual manipulators to handle dynamic obstacles has garnered 100 citations, while subsequent work incorporating Q-learning for congested environments (38 citations) and deep Q-networks for narrow-road navigation (29 citations) demonstrates his commitment to advancing intelligent, real-world-ready robotic systems. Motoi has also made notable contributions to humanoid robotics, proposing the Virtual Linear Inverted Pendulum Mode for bipedal locomotion planning (67 citations) and developing real-time gait strategies for humanoid pushing tasks (39 citations). His work on force-based variable compliance controllers (42 citations) and bilateral control systems further reflects his expertise in flexible, safe human-robot interaction. Across his career, Motoi has consistently bridged theoretical frameworks with practical implementation, addressing challenges such as teleoperation, blind-spot awareness, and unknown object manipulation. With over 370 cumulative citations, his research continues to shape the landscape of autonomous and humanoid robotics.
Research Focus
Key Achievements
Top Papers
- 1
- 2A Bipedal Locomotion Planning Based on Virtual Linear Inverted Pendulum Mode67 citations · 2008
- 3
- 4Real-Time Gait Planning for Pushing Motion of Humanoid Robot39 citations · 2007
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- 7Bilateral control with different inertia based on modal decomposition21 citations · 2010
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