Junichi Nagasue
Papers
1
Total Citations
9
H-Index
1
About
Junichi Nagasue is a robotics researcher whose work centers on bipedal locomotion and adaptive walking control for humanoid robots. His key research areas include real-time gait generation, environmental adaptation, and machine learning applications in robotics. Nagasue's most notable contribution is his pioneering work on slope-walking for biped robots, where he proposed a novel walking pattern generation method using the K Nearest Neighbor (K-NN) algorithm. This approach enables bipedal robots to dynamically compensate for environmental changes, such as walking on slopes, by pre-recording walking paths into a database and selecting the most suitable one in real-time. His 2009 paper on this method has garnered 9 citations, demonstrating its foundational role in adaptive locomotion research. Nagasue's work bridges the gap between offline path planning and online adaptation, offering a practical solution for robots navigating uneven terrains. His contributions are particularly valuable for advancing humanoid robotics in real-world applications, where environmental unpredictability remains a key challenge.
Research Focus
Key Achievements
Top Papers
- 1Slope-Walking of a Biped Robot with K Nearest Neighbor method9 citations · 2009